Logic has been a—disputed—ingredient in the emergence and development of the now very large field known as knowledge representation and reasoning. In this book (in progress), I select some central topics in this highly fruitful, albeit controversial, association (e.g., non-monotonic reasoning, implicit belief, logical omniscience, closed world assumption), identifying their sources and analyzing/explaining their elaboration in highly influential published work.

This paper briefly outlines some advancements in paraconsistent logics for modelling knowledge representation and reasoning. Emphasis is given on the so-called Logics of Formal Inconsistency (LFIs), a class of paraconsistent logics that formally internalize the very concept(s) of consistency and inconsistency. A couple of specialized systems based on the LFIs will be reviewed, including belief revision and probabilistic reasoning. Potential applications of those systems in the AI area of KRR are tackled by illustrating some examples that (...) emphasizes the importance of a fine-tuned treatment of consistency in modelling reputation systems, preferences, argumentation, and evidence. (shrink)

Formal ontologies are nowadays widely considered a standard tool for knowledge representation and reasoning in the Semantic Web. In this context, they are expected to play an important role in helping automated processes to access information. Namely: they are expected to provide a formal structure able to explicate the relationships between different concepts/terms, thus allowing intelligent agents to interpret, correctly, the semantics of the web resources improving the performances of the search technologies. Here we take into account (...) a problem regarding Knowledge Representation in general, and ontology based representations in particular; namely: the fact that knowledge modeling seems to be constrained between conflicting requirements, such as compositionality, on the one hand and the need to represent prototypical information on the other. In particular, most common sense concepts seem not to be captured by the stringent semantics expressed by such formalisms as, for example, Description Logics (which are the formalisms on which the ontology languages have been built). The aim of this work is to analyse this problem, suggesting a possible solution suitable for formal ontologies and semantic web representations. The questions guiding this research, in fact, have been: is it possible to provide a formal representational framework which, for the same concept, combines both the classical modelling view (accounting for compositional information) and defeasible, prototypical knowledge ? Is it possible to propose a modelling architecture able to provide different type of reasoning (e.g. classical deductive reasoning for the compositional component and a non monotonic reasoning for the prototypical one)? We suggest a possible answer to these questions proposing a modelling framework able to represent, within the semantic web languages, a multilevel representation of conceptual information, integrating both classical and non classical (typicality based) information. Within this framework we hypothesise, at least in principle, the coexistence of multiple reasoning processes involving the different levels of representation. (shrink)

Schemes of diagrammatic representation have been so familiarly introduced into logical treatises during the last century or so, that many readers, even of those who have made no professional study of logic, may be supposed to be acquainted with the general nature and object of such devices. Of these schemes one only, viz. that commonly called "Eulerian circles," has met with any general acceptance. A variety of others indeed have been proposed by ingenious and celebrated logicians, several of which (...) would claim notice in a historical treatment of the subject; but they mostly do not seem to me to differ in any essential respect from that of Euler. They rest upon the same leading principle, and are subject all alike to the same restrictions and defects. We must therefore cast about for some new scheme of diagrammatic representation which shall be competent to indicate imperfect knowledge on our part; for this will at once enable us to appeal to it step by step in the process of working out our conclusions. I have never seen any hint at such a scheme, though the want seems so evident that one would suppose that something of the kind must have been proposed before. (shrink)

In this article we present an advanced version of Dual-PECCS, a cognitively-inspired knowledge representation and reasoning system aimed at extending the capabilities of artificial systems in conceptual categorization tasks. It combines different sorts of common-sense categorization (prototypical and exemplars-based categorization) with standard monotonic categorization procedures. These different types of inferential procedures are reconciled according to the tenets coming from the dual process theory of reasoning. On the other hand, from a representational perspective, the system relies on (...) the hypothesis of conceptual structures represented as heterogeneous proxytypes. Dual-PECCS has been experimentally assessed in a task of conceptual categorization where a target concept illustrated by a simple common-sense linguistic description had to be identified by resorting to a mix of categorization strategies, and its output has been compared to human responses. The obtained results suggest that our approach can be beneficial to improve the representational and reasoning conceptual capabilities of standard cognitive artificial systems, and –in addition– that it may be plausibly applied to different general computational models of cognition. The current version of the system, in fact, extends our previous work, in that Dual-PECCS is now integrated and tested into two cognitive architectures, ACT-R and CLARION, implementing different assumptions on the underlying invariant structures governing human cognition. Such integration allowed us to extend our previous evaluation. (shrink)

We describe and try to motivate our project to build systems using both a knowledge based and a neural network approach. These two approaches are used at different stages in the solution of a problem, instead of using knowledge bases exclusively on some problems, and neural nets exclusively on others. The knowledge base (KB) is defined first in a declarative, symbolic language that is easy to use. It is then compiled into an efficient neural network (NN) (...) class='Hi'>representation, run, and the results from run time and (eventually) from learning are decompiled to a symbolic description of the knowledge contained in the network. After inspecting this recovered knowledge, a designer would be able to modify the KB and go through the whole cycle of compiling, running, and decompiling again. The central question with which this project is concerned is, therefore, How do we go from a KB to an NN, and back again? We are investigating this question by building tools consisting of a repertoire of language/translation/network types, and trying them on problems in a variety of domains. (shrink)

We discuss the role of perceptron (or threshold) connectives in the context of Description Logic, and in particular their possible use as a bridge between statistical learning of models from data and logical reasoning over knowledge bases. We prove that such connectives can be added to the language of most forms of Description Logic without increasing the complexity of the corresponding inference problem. We show, with a practical example over the Gene Ontology, how even simple instances of perceptron (...) connectives are expressive enough to represent learned, complex concepts derived from real use cases. This opens up the possibility to import concepts learnt from data into existing ontologies. (shrink)

The paper introduces an extension of the proposal according to which conceptual representations in cognitive agents should be intended as heterogeneous proxytypes. The main contribution of this paper is in that it details how to reconcile, under a heterogeneous representational perspective, different theories of typicality about conceptual representation and reasoning. In particular, it provides a novel theoretical hypothesis - as well as a novel categorization algorithm called DELTA - showing how to integrate the representational and reasoning assumptions (...) of the theory-theory of concepts with the those ascribed to the prototype and exemplars-based theories. (shrink)

We present a computational analysis of de re, de dicto, and de se belief and knowledge reports. Our analysis solves a problem first observed by Hector-Neri Castañeda, namely, that the simple rule -/- `(A knows that P) implies P' -/- apparently does not hold if P contains a quasi-indexical. We present a single rule, in the context of a knowledge-representation and reasoning system, that holds for all P, including those containing quasi-indexicals. In so doing, we explore (...) the difference between reasoning in a public communication language and in a knowledge-representation language, we demonstrate the importance of representing proper names explicitly, and we provide support for the necessity of considering sentences in the context of extended discourse (for example, written narrative) in order to fully capture certain features of their semantics. (shrink)

[Significantly updated in Chapter 6 of Awareness and the Substructure of Knowledge] In order for a reason to justify an action or attitude it must be one that is possessed by an agent. Knowledge-centric views of possession ground our possession of reasons, at least partially, either in our knowledge of them or in our being in a position to know them. On virtually all accounts, knowing P is some kind of non-accidental true belief that P. This entails (...) that knowing P is a kind of non-accidental true representation that P. I outline a novel theory of the epistemic requirement on possession in terms of this more general state of non-accidental true representation. It is just as well placed to explain the motivations behind knowledge-centric views of possession, and it is also better placed to explain the extent of the reasons we possess in certain cases of deductive belief-updates and cases involving environmental luck. I conclude with three reflections. First, I indicate how my arguments generate a dilemma for Errol Lord’s view that possessing reasons is just a matter of being in a position to manifest one’s knowledge how to use them. Second, I explain how my view can simultaneously manage cases of environmental luck without falling prey to lottery cases. Finally, I sketch the direction for a further range of counterexamples to knowledge-centric theories of possession. (shrink)

While philosophers hold that it is patently absurd to blame robots or hold them morally responsible [1], a series of recent empirical studies suggest that people do ascribe blame to AI systems and robots in certain contexts [2]. This is disconcerting: Blame might be shifted from the owners, users or designers of AI systems to the systems themselves, leading to the diminished accountability of the responsible human agents [3]. In this paper, we explore one of the potential underlying reasons for (...) robot blame, namely the folk's willingness to ascribe inculpating mental states or "mens rea" to robots. In a vignette-based experiment (N=513), we presented participants with a situation in which an agent knowingly runs the risk of bringing about substantial harm. We manipulated agent type (human v. group agent v. AI-driven robot) and outcome (neutral v. bad), and measured both moral judgment (wrongness of the action and blameworthiness of the agent) and mental states attributed to the agent (recklessness and the desire to inflict harm). We found that (i) judgments of wrongness and blame were relatively similar across agent types, possibly because (ii) attributions of mental states were, as suspected, similar across agent types. This raised the question - also explored in the experiment - whether people attribute knowledge and desire to robots in a merely metaphorical way (e.g., the robot "knew" rather than really knew). However, (iii), according to our data people were unwilling to downgrade to mens rea in a merely metaphorical sense when given the chance. Finally, (iv), we report a surprising and novel finding, which we call the inverse outcome effect on robot blame: People were less willing to blame artificial agents for bad outcomes than for neutral outcomes. This suggests that they are implicitly aware of the dangers of overattributing blame to robots when harm comes to pass, such as inappropriately letting the responsible human agent off the moral hook. (shrink)

Review of Joseph Y. Halpern (ed.), Theoretical Aspects of Reasoning About Knowledge: Proceedings of the 1986 Conference (Los Altos, CA: Morgan Kaufmann, 1986),.

In philosophy of music, formalists argue that pure instrumental music is unable to represent any content without the help of lyrics, titles, or dramatic context. In particular, they deny that music’s use of convention counts as a genuine case of representation because only intrinsic means of representing counts and conventions are extrinsic to the sound structures making up music. In this paper, I argue that convention should count as a way for music to genuinely represent content for two reasons. (...) First, the view that only intrinsic ways of representing counts is too stringent. If use can ground meaning in language, then use might also ground meaning (and representation) in music, too. Second, even if we were to insist on intrinsic features, convention should count as a way for music to genuinely represent because convention is an intrinsic feature of music. Without knowledge of musical systems and encultured listening, music wouldn’t even be recognized as music, so convention is already baked into our listening practices. (shrink)

This paper challenges the first Gettier counterexample to the tripartite account of knowledge. Noting that 'the man who will get the job' is a description and invoking Donnellan's distinction between their 'referential' and 'attributive' uses, I argue that Smith does not actually believe that the man who will get the job has ten coins in his pocket. Smith's ignorance about who will get the job shows that the belief cannot be understood referentially, his ignorance of the coins in his (...) pocket shows that it cannot be understood attributively. An explanation for why Smith appeared to have justified true belief is given by distinguishing between 'belief' and 'belief in truth'. Smith believes the sentence 'the man who will get the job has ten coins in his pocket' to be true (he mistakenly believes that Jones will get the job, of whom he knows that he has ten coins in his pocket) (hence his 'belief'), the sentence is true (hence 'truth'), and he has sufficient reason to assent to it (hence his 'justification'). But he does not believe the proposition expressed. Hence he does not know it either. (shrink)

We introduce and discuss a knowledge-driven distillation approach to explaining black-box models by means of two kinds of interpretable models. The first is perceptron (or threshold) connectives, which enrich knowledge representation languages such as Description Logics with linear operators that serve as a bridge between statistical learning and logical reasoning. The second is Trepan Reloaded, an ap- proach that builds post-hoc explanations of black-box classifiers in the form of decision trees enhanced by domain knowledge. Our (...) aim is, firstly, to target a model-agnostic distillation approach exemplified with these two frameworks, secondly, to study how these two frameworks interact on a theoretical level, and, thirdly, to investigate use-cases in ML and AI in a comparative manner. Specifically, we envision that user-studies will help determine human understandability of explanations generated using these two frameworks. (shrink)

[Significantly updated in Chapter 7 of Awareness and the Substructure of Knowledge] Many have found it plausible that knowledge is a constitutively normative state, i.e. a state that is grounded in the possession of reasons. Many have also found it plausible that certain cases of proprioceptive knowledge, memorial knowledge, and self-evident knowledge are cases of knowledge that are not grounded in the possession of reasons. I refer to these as cases of basic knowledge. (...) The existence of basic knowledge forms a primary objection to the idea that knowledge is a constitutively normative state. In what follows I offer a way through the apparent dilemma of having to choose between either basic knowledge or the normativity of knowledge. The solution involves homing in on a state of awareness (≈non-accidental true representation) that is distinct from knowledge and which in turn grounds the normativity of knowledge in a way that is fully consistent with the existence of basic knowledge. An upshot of this is that externalist theories of knowledge turn out to be fully compatible with the thesis that knowledgeable beliefs are always beliefs that are justified by the reasons one possesses. (shrink)

A. Newell and H. A. Simon were two of the most influential scientists in the emerging field of artificial intelligence (AI) in the late 1950s through to the early 1990s. This paper reviews their crucial contribution to this field, namely to symbolic AI. This contribution was constituted mostly by their quest for the implementation of general intelligence and (commonsense) knowledge in artificial thinking or reasoning artifacts, a project they shared with many other scientists but that in their case (...) was theoretically based on the idiosyncratic notions of symbol systems and the representational abilities they give rise to, in particular with respect to knowledge. While focusing on the period 1956-1982, this review cites both earlier and later literature and it attempts to make visible their potential relevance to today's greatest unifying AI challenge, to wit, the design of wholly autonomous artificial agents (a.k.a. robots) that are not only rational and ethical, but also self-conscious. (shrink)

A 3rd person Knowledge Level analysis of cognitive architectures -/- Abstract I provide a knowledge level analysis of the main representational and reasoning problems affecting the cognitive architectures for what concerns this issue. In providing this analysis I will show, by considering some of the main cognitive architectures currently available (e.g. SOAR, ACT-R, CLARION), how one of the main problems of such architectures is represented by the fact that their knowledge representation and processing mechanisms are (...) not sufficiently constrained with “structural insights” (Lieto 2021) coming from cognitive science for dealing with commonsense knowledge and reasoning (Lebiere, Oltramari, 2018). As a possible way out to such knowledge processing issues, I present the main assumptions that have led to the development of the Dual PECCS categorization system (Lieto, Radicioni, Rho 2017) and discuss some of the lessons learned and their possible implications in the design of the knowledge modules and knowledge-processing mechanisms of integrated cognitive architectures. (shrink)

This essay presents a philosophical and computational theory of the representation of de re, de dicto, nested, and quasi-indexical belief reports expressed in natural language. The propositional Semantic Network Processing System (SNePS) is used for representing and reasoning about these reports. In particular, quasi-indicators (indexical expressions occurring in intentional contexts and representing uses of indicators by another speaker) pose problems for natural-language representation and reasoning systems, because--unlike pure indicators--they cannot be replaced by coreferential NPs without changing (...) the meaning of the embedding sentence. Therefore, the referent of the quasi-indicator must be represented in such a way that no invalid coreferential claims are entailed. The importance of quasi-indicators is discussed, and it is shown that all four of the above categories of belief reports can be handled by a single representational technique using belief spaces containing intensional entities. Inference rules and belief-revision techniques for the system are also examined. (shrink)

During the last decades, many cognitive architectures (CAs) have been realized adopting different assumptions about the organization and the representation of their knowledge level. Some of them (e.g. SOAR [35]) adopt a classical symbolic approach, some (e.g. LEABRA[ 48]) are based on a purely connectionist model, while others (e.g. CLARION [59]) adopt a hybrid approach combining connectionist and symbolic representational levels. Additionally, some attempts (e.g. biSOAR) trying to extend the representational capacities of CAs by integrating diagrammatical representations and (...) reasoning are also available [34]. In this paper we propose a reflection on the role that Conceptual Spaces, a framework developed by Peter G¨ardenfors [24] more than fifteen years ago, can play in the current development of the Knowledge Level in Cognitive Systems and Architectures. In particular, we claim that Conceptual Spaces offer a lingua franca that allows to unify and generalize many aspects of the symbolic, sub-symbolic and diagrammatic approaches (by overcoming some of their typical problems) and to integrate them on a common ground. In doing so we extend and detail some of the arguments explored by G¨ardenfors [23] for defending the need of a conceptual, intermediate, representation level between the symbolic and the sub-symbolic one. In particular we focus on the advantages offered by Conceptual Spaces (w.r.t. symbolic and sub-symbolic approaches) in dealing with the problem of compositionality of representations based on typicality traits. Additionally, we argue that Conceptual Spaces could offer a unifying framework for interpreting many kinds of diagrammatic and analogical representations. As a consequence, their adoption could also favor the integration of diagrammatical representation and reasoning in CAs. (shrink)

Orthodox epistemological disjunctivism involves the idea that paradigm cases of visual perceptual knowledge are based on visual perceptual states which are propositional, and hence representational. Given this, the orthodox version of epistemological disjunctivism takes on controversial representational commitments in the philosophy of perception. Must epistemological disjunctivism involve these commitments? I don’t think so. Here I argue that we can take epistemological disjunctivism in a new direction and develop a version of the view free of these representational commitments. The basic (...) idea is that instead of conceiving of knowledge grounding perceptions as states in which one sees that such-and-such is the case, we should instead conceive of them as states or episodes in which one sees a thing, we should conceive of them as thing-seeings. I’ll suggest that we can cast such seeings in a knowledge grounding role without conceiving of them as representational. But this is because we can put thing-seeings to epistemological work, in the framework of epistemological disjunctivism, whilst remaining neutral on whether or not they are propositional, or representational at all. The point, then, is not to replace epistemological disjunctivism’s controversial representational commitments with controversial non-representational commitments. The point is, rather, that epistemological disjunctivism can be developed with fewer commitments in the philosophy of perception than is usually appreciated. (shrink)

The essays in this volume explore those aspects of Kant’s writings which concern issues in the philosophy of mind. These issues are central to any understanding of Kant’s critical philosophy and they bear upon contemporary discussions in the philosophy of mind. Fourteen specially written essays address such questions as: What role does mental processing play in Kant’s account of intuition? What kinds of empirical models can be given of these operations? In what sense, and in what ways, are intuitions object-dependent? (...) How should we understand the nature of the imagination? What is inner sense, and what does it mean to say that time is the form of inner sense? Can we cognize ourselves through inner sense? How do we self-ascribe our beliefs and what role does self-consciousness play in our judgments? Is the will involved in judging? What kind of knowledge can we have of the self ? And what kind of knowledge of the self does Kant proscribe? These essays showcase the depth of Kant’s writings in the philosophy of mind, and the centrality of those writings to his wider philosophical project. Moreover, they show the continued relevance of Kant’s writings to contemporary debates about the nature of mind and self. Contents: 0. Introduction Anil Gomes and Andrew Stephenson 1. Kant, The Philosophy Of Mind, And Twentieth Century Analytic Philosophy Anil Gomes 2. Synthesis And Binding Lucy Allais 3. Understanding Non-Conceptual Representation Of Objects: Empirical Models Of Sensibility’s Operation Katherine Dunlop 4. Are Kantian Intuitions Object-Dependent? Stefanie Grüne 5. Intuition And Presence Colin McLear 6. Imagination And Inner Intuition Andrew Stephenson 7. Inner Sense And Time Ralf M. Bader 8. Can’t Kant Cognize Himself? Or, A Problem For (Almost) Every Interpretation Of The Refutation Of Idealism Andrew Chignell 9. A Kantian Critique Of Transparency Patricia Kitcher 10. Judging For Reasons: On Kant And The Modalities Of Judgment Jessica Leech 11. Kant On Judging And The Will Jill Vance Buroker 12. Self and Selves Ralph C. S. Walker 13. Subjects Of Kant’s First Paralogism Tobias Rosefeldt 14. The Lessons Of Kant’s Paralogisms Paul Snowdon. (shrink)

The paper presents the heterogeneous proxytypes hypothesis as a cognitively-inspired computational framework able to reconcile, in both natural and artificial systems, different theories of typicality about conceptual representation and reasoning that have been traditionally seen as incompatible. In particular, through the Dual PECCS system and its evolution, it shows how prototypes, exemplars and theory-theory like conceptual representations can be integrated in a cognitive artificial agent (thus extending its categorization capabilities) and, in addition, can provide useful insights in the (...) context of a computationally grounded science of the mind. (shrink)

I argue for three points: First, evidence of the primacy of knowledge representation is not evidence of primacy of knowledge. Second, knowledge-oriented mindreading research should also focus on misrepresentations and biased representations of knowledge. Third, knowledge-oriented mindreading research must confront the problem of the gold standard that arises when disagreement about knowledge complicates the interpretation of empirical findings.

The idea that pictorial art can have cognitive value, that it can enhance our understanding of the world and of our own selves, has had many advocates in art theory and philosophical aesthetics alike. It has also been argued, however, that the power of pictorial representation to convey or enhance knowledge, in particular knowledge with moral content, is not generalized across the medium.

Cognitive agents, whether human or computer, that engage in natural-language discourse and that have beliefs about the beliefs of other cognitive agents must be able to represent objects the way they believe them to be and the way they believe others believe them to be. They must be able to represent other cognitive agents both as objects of beliefs and as agents of beliefs. They must be able to represent their own beliefs, and they must be able to represent beliefs (...) as objects of beliefs. These requirements raise questions about the number of tokens of the belief representation language needed to represent believers and propositions in their normal roles and in their roles as objects of beliefs. In this paper, we explicate the relations among nodes, mental tokens, concepts, actual objects, concepts in the belief spaces of an agent and the agent's model of other agents, concepts of other cognitive agents, and propositions. We extend, deepen, and clarify our theory of intensional knowledge representation for natural-language processing, as presented in previous papers and in light of objections raised by others. The essential claim is that tokens in a knowledge-representation system represent only intensions and not extensions. We are pursuing this investigation by building CASSIE, a computer model of a cognitive agent and, to the extent she works, a cognitive agent herself. CASSIE's mind is implemented in the SNePS knowledge-representation and reasoning system. (shrink)

The notion of relevance plays a role in many accounts of knowledge and knowledge ascription. Although use of the notion is well-motivated, theorists struggle to codify relevance. A reasonable person standard of relevance addresses this codification problem, and provides an objective and flexible standard of relevance; however, treating relevance as reasonableness seems to allow practical factors to determine whether one has knowledge or not—so-called “pragmatic encroachment.” I argue that a fuller understanding of reasonableness and of the role (...) of practical factors in the acquisition of knowledge lets us avoid pragmatic encroachment. (shrink)

This chapter describes Spinoza's obscure “ideas of ideas” doctrine and his claim that “as soon as one knows something, one knows that one knows it, and simultaneously knows that one knows that one knows, and so on, to infinity”. Spinoza holds that the human mind is a representation of the body: the “objectum of the idea constituting the human mind” is the human body. Suppose ideas are essentially self‐reflexive, and that this reflexive awareness, the “idea of the idea,” makes (...) the objectively‐real representational content present to mind. The chapter also suggests that Spinoza holds that adequate ideas come, by nature, with reflective knowledge. Reasoning through the Ethics is one way to come to the adequate ideas that silence doubts about the veridicality of one's adequate ideas of bodies. The “human mind has an adequate cognition of God's eternal and infinite essence”. (shrink)

This project continues our interdisciplinary research into computational and cognitive aspects of narrative comprehension. Our ultimate goal is the development of a computational theory of how humans understand narrative texts. The theory will be informed by joint research from the viewpoints of linguistics, cognitive psychology, the study of language acquisition, literary theory, geography, philosophy, and artificial intelligence. The linguists, literary theorists, and geographers in our group are developing theories of narrative language and spatial understanding that are being tested by the (...) cognitive psychologists and language researchers in our group, and a computational model of a reader of narrative text is being developed by the AI researchers, based in part on these theories and results and in part on research on knowledge representation and reasoning. This proposal describes the knowledge-representation and natural-language-processing issues involved in the computational implementation of the theory; discusses a contrast between communicative and narrative uses of language and of the relation of the narrative text to the story world it describes; investigates linguistic, literary, and hermeneutic dimensions of our research; presents a computational investigation of subjective sentences and reference in narrative; studies children’s acquisition of the ability to take third-person perspective in their own storytelling; describes the psychological validation of various linguistic devices; and examines how readers develop an understanding of the geographical space of a story. This report is a longer version of a project description submitted to NSF. This document, produced in May 2007, is a L ATEX version of Technical Report 89-07 (Buffalo: SUNY Buffalo Department of Computer Science, August 1989), with slightly.. (shrink)

Standpoint logic is a recently proposed formalism in the context of knowledge integration, which advocates a multi-perspective approach permitting reasoning with a selection of diverse and possibly conflicting standpoints rather than forcing their unification. In this paper, we introduce nested sequent calculi for propositional standpoint logics---proof systems that manipulate trees whose nodes are multisets of formulae---and show how to automate standpoint reasoning by means of non-deterministic proof-search algorithms. To obtain worst-case complexity-optimal proof-search, we introduce a novel technique (...) in the context of nested sequents, referred to as "coloring," which consists of taking a formula as input, guessing a certain coloring of its subformulae, and then running proof-search in a nested sequent calculus on the colored input. Our technique lets us decide the validity of standpoint formulae in CoNP since proof-search only produces a partial proof relative to each permitted coloring of the input. We show how all partial proofs can be fused together to construct a complete proof when the input is valid, and how certain partial proofs can be transformed into a counter-model when the input is invalid. These "certificates" (i.e. proofs and counter-models) serve as explanations of the (in)validity of the input. (shrink)

Much recent cognitive neuroscientific work on body knowledge is representationalist: “body schema” and “body images”, for example, are cerebral representations of the body (de Vignemont 2009). A framework assumption is that representation of the body plays an important role in cognition. The question is whether this representationalist assumption is compatible with the variety of broadly situated or embodied approaches recently popular in the cognitive neurosciences: approaches in which cognition is taken to have a ‘direct’ relation to the body (...) and to the environment. A “direct” relation is one where the boundaries between the body and the head, or between the environment and the animal are not theoretically important in the understanding of cognition. These boundaries do not play a theoretically privileged role in cognitive explanations of behavior. But representationalism appears to put a representational veil between the locus of cognition and that which is represented, making cognitive relations to the body and to the environment be indirect, with a high associated computational load. For this reason, direct approaches have tried to minimize the use of internal representations (Suchman 1987; Barwise 1987; Agre and Chapman 1987; Brooks 1992; Thelen and Smith 1994; van Gelder 1995; Port and van Gelder 1995; Clark 1997, 1999; Rupert 2009, p. 180). Does a cognitive neuroscience committed to direct relations rule out a representationalist approach to body knowledge? Or is direct representationalism possible? (shrink)

In Naturalizing the Mind, Fred Dretske articulates and defends a naturalistic theory of the mind which he calls «the Representation Thesis.» In brief, this thesis states that «(1) All mental facts are representational facts, and (2) All representational facts are facts about information functions.» From this it follows that introspective knowledge, the mind's direct knowledge of its own states, is a case of «displaced perception»-that is, knowledge of mental (i.e., representational) facts through an awareness of external (...) (i.e., physical) objects. In an earlier work, Dretske presents a general account of knowledge which is intended to circumvent Gettier-type counterexamples. According to this view, S knows that P if and only if: (1) S believes, without doubt, reservation, or question, that P is the case; (2) P is the case; (3) S has a reason, R, for believing that P such that, if P were not the case, then S would not have R (i.e., S has a conclusive reason, R, for believing that P). In this paper, my aim is to explore the relation between these two theories. After summarizing both in brief detail, I argue that Dretske's account of introspective knowledge cannot be reconciled with his account of knowledge broadly construed. (shrink)

Despite the efforts undertaken to separate scientific reasoning and metaphysical considerations, despite the rigor of construction of mathematics, these are not, in their very foundations, independent of the modalities, of the laws of representation of the world. The OdC shows that the logical Facts Exist neither more nor less than the Facts of the world which are Facts of Knowledge. Mathematical facts are representation facts. The primary objective of this article is to integrate the subject into (...) mathematics as a mode of emergence of meaning and then to evaluate its consequences. (shrink)

Several philosophers have proposed Knowledge-Based Decision Theories (KDTs)—theories that require agents to maximize expected utility as yielded by utility and probability functions that depend on the agent’s knowledge. Proponents of KDTs argue that such theories are motivated by Knowledge-Reasons norms that require agents to act only on reasons that they know. However, no formal derivation of KDTs from Knowledge-Reasons norms has been suggested, and it is not clear how such norms justify the particular ways in which (...) KDTs relate knowledge and rational action. In this paper, I suggest a new axiomatic method for justifying KDTs and providing them with stronger normative foundations. I argue that such theories may be derived from constraints on the relation between knowledge and preference, and that these constraints may be evaluated relative to intuitions regarding practical reasoning. To demonstrate this, I offer a representation theorem for a KDT proposed by Hawthorne and Stanley (2008) and briefly evaluate it through its underlying axioms. -/- In section 1, I present knowledge-based decision theories generally and the versions of such theories suggested in the literature. In section 2, I argue that KDTs and theories of practical reasoning conjoined with Knowledge-Reasons norms generate constraints on the same relation—the relation between knowledge and preference. In section 3, I present a formal framework in which constraints on this relation may be expressed and from which KDTs may be derived. In section 4, I present a representation theorem for a specific KDT. In section 5, I briefly evaluate the axioms of the theory, and in section 6, I conclude. (shrink)

Kant holds that the whole “higher faculty of knowledge” (‘reason’ or ‘understanding’ in a broad sense), is a spontaneous faculty. But what could this mean? It seems that it could either be a perfectly innocent claim or a very dangerous one. The innocent thought is that reason is spontaneous because it is not wholly passive, not just a slave to what bombards the senses. If so, then the rejection of Hume’s radical empiricism would suffice for Kant’s claim. But the (...) dangerous thought is that reason, and the ‘I think’ which expresses it, is free, having the power to produce something entirely from itself. While this freedom is characteristic of practical reason, could it be characteristic of reason in general, even in its theoretical employment? Some contemporary interpreters have admirably defended the ‘dangerous’ conception by stripping it of the implication that it makes reason in general entirely self-sufficient. I attempt to add to this effort. However, what I contend is that this weightier conception of spontaneity (‘absolute’ or ‘non-relative’ spontaneity) requires abandoning a certain approach to the question that has been assumed by virtually everyone in the debate—namely, that the question can be answered by siding with either the so-called ‘metaphysical’ or the ‘epistemic’ interpreters of Kant. My goal is to suggest that the proper perspective on reason’s spontaneity resists such characterizations all together, and thereby resists any of the conditions under which it could be understood as ‘relative’ to anything. (shrink)

We present a preliminary high-level formal theory, grounded on knowledge representation techniques and foundational ontologies, for the uniform and integrated representation of the different kinds of (quali- tative and quantitative) knowledge involved in the designing process. We discuss the conceptual nature of engineering design by individuating and analyzing the involved notions. These notions are then formally charac- terized by extending the DOLCE foundational ontology. Our ultimate purpose is twofold: (i) to contribute to foundational issues of design; (...) and (ii) to support the development of advanced modelling systems for (qualitative and quantitative) representation of design knowledge. (shrink)

An early, very preliminary edition of this book was circulated in 1962 under the title Set-theoretical Structures in Science. There are many reasons for maintaining that such structures play a role in the philosophy of science. Perhaps the best is that they provide the right setting for investigating problems of representation and invariance in any systematic part of science, past or present. Examples are easy to cite. Sophisticated analysis of the nature of representation in perception is to be (...) found already in Plato and Aristotle. One of the great intellectual triumphs of the nineteenth century was the mechanical explanation of such familiar concepts as temperature and pressure by their representation in terms of the motion of particles. A more disturbing change of viewpoint was the realization at the beginning of the twentieth century that the separate invariant properties of space and time must be replaced by the space-time invariants of Einstein's special relativity. Another example, the focus of the longest chapter in this book, is controversy extending over several centuries on the proper representation of probability. The six major positions on this question are critically examined. Topics covered in other chapters include an unusually detailed treatment of theoretical and experimental work on visual space, the two senses of invariance represented by weak and strong reversibility of causal processes, and the representation of hidden variables in quantum mechanics. The final chapter concentrates on different kinds of representations of language, concluding with some empirical results on brain-wave representations of words and sentences. (shrink)

Our epistemology can shape the way we think about perception and experience. Speaking as an epistemologist, I should say that I don’t necessarily think that this is a good thing. If we think that we need perceptual evidence to have perceptual knowledge or perceptual justification, we will naturally feel some pressure to think of experience as a source of reasons or evidence. In trying to explain how experience can provide us with evidence, we run the risk of either adopting (...) a conception of evidence according to which our evidence isn’t very much like the objects of our beliefs that figure in reasoning (e.g., by identifying our evidence with experiences or sensations) or the risk of accepting a picture of experience according to which our perceptions and perceptual experiences are quite similar to beliefs in terms of their objects and their representational powers. But I think we have good independent reasons to resist identifying our evidence with things that don’t figure in our reasoning as premises and I think we have good independent reason to doubt that experience is sufficiently belief-like to provide us with something premise-like that can figure in reasoning. We should press pause. We shouldn’t let questionable epistemological assumptions tell us how to do philosophy of mind. I don’t think that we have good reason to think that we need the evidence of the senses to explain how perceptual justification or knowledge is possible. Part of my scepticism derives from the fact that I think we can have kinds of knowledge where the relevant knowledge is not evidentially grounded. Part of my scepticism derives from the fact that there don’t seem to be many direct arguments for thinking that justification and knowledge always requires evidential support. In this paper, I shall consider the three arguments I’ve found for thinking that justification and knowledge do always require evidential support and explain why I don’t find them convincing. I think that we can explain perceptual justification, rationality, and defeat without assuming that our experiences provide us with evidence. In the end, I think we can partially vindicate Davidson’s (notorious) suggestion that our beliefs, not experiences, provide us with reasons for forming further beliefs. This idea turns out to be compatible with foundationalism once we understand that foundational status can come from something other than evidential support. (shrink)

The engineering knowledge research program is part of the larger effort to articulate a philosophy of engineering and an engineering worldview. Engineering knowledge requires a more comprehensive conceptual framework than scientific knowledge. Engineering is not ‘merely’ applied science. Kuhn and Popper established the limits of scientific knowledge. In parallel, the embrace of complementarity and uncertainty in the new physics undermined the scientific concept of observer-independent knowledge. The paradigm shift from the scientific framework to the broader (...) participant engineering framework entails a problem shift. The detached scientific spectator seeks the ‘facts’ of ‘objective’ reality – out there. The participant, embodied in reality, seeks ‘methods’, about how to work in the world. The engineering knowledge research program is recursively enabling. Advances in engineering knowledge are involved in the unfolding of the nature of reality. Newly understood, quantum uncertainty entails that the participant is a natural inquirer. ‘Practical reason’ is concerned with ‘how we should live’– the defining question of morality. The engineering knowledge research program is selective seeking ‘important truths’, ‘important knowledge’, ‘important methods’ that manifest value, and serve the engineering agenda of ‘the construction of the good.’ The importance of engineering knowledge research program is clear in the new STEM curriculum where educators have been challenged to rethink the relation between science and engineering. A 2015 higher education initiative to integrate engineering colleges into liberal arts and sciences colleges has stalled due to the confusion and conflict between the engineering and scientific representations of knowledge. (shrink)

In this inaugural lecture I offer, against the background of a discussion of knowledge representation and its tools, an overview of my research in the philosophy of science. I defend a relational model-theoretic realism as being the appropriate meta-stance most congruent with the model-theoretic view of science as a form of human engagement with the world. Making use of logics with preferential semantics within a model-theoretic paradigm, I give an account of science as process and product. I demonstrate (...) the power of the full-blown employment of this paradigm in the philosophy of science by discussing the main applications of model-theoretic realism to traditional problems in the philosophy of science. I discuss my views of the nature of logic and of its role in the philosophy of science today. I also specifically offer a brief discussion on the future of cognitive philosophy in South Africa. My conclusion is a general look at the nature of philosophical inquiry and its significance for philosophers today. South African Journal of Philosophy Vol. 25 (4) 2006: pp. 275-289. (shrink)

I reply to criticisms from King and Soames and critically examine two aspects of current orthodoxy about propositions: that they are representational and that they are structured. I argue that (especially once one gives up on intrinsically representational propositions) there is no good reason to think that propositions have representational properties, and distinguish a few different senses in which propositions might be structured, expressing some skepticism about the more ambitious ones.

Mark Schroeder’s Reasons First is admirable in its scope and execution, deftly demonstrating the theoretical promise of extending the reasons-first approach from ethics to epistemology. In what follows we explore how (not) to account for the evidence-that relation within the reasons-first program, we explain how factive content views of evidence can be resilient in the face of Schroeder’s criticisms, and we explain how knowledge from falsehood threatens Schroeder’s view of knowledge. Along the way we sketch a reliabilist account (...) of the reasons-for relation (inspired by Alston) and show how it limits the applicability of Schroeder’s arguments. (shrink)

I address a type of circularity threat that arises for the view that we employ general basic logical principles in deductive reasoning. This type of threat has been used to argue that whatever knowing such principles is, it cannot be a fully cognitive or propositional state, otherwise deductive reasoning would not be possible. I look at two versions of the circularity threat and answer them in a way that both challenges the view that we need to apply general (...) logical principles in deductive reasoning and defuses the threat to a cognitivist account of knowing basic logical principles. (shrink)

Approximation involves representing things in ways that might be close to the truth but are nevertheless false. Given the widespread reliance on approximations in science and everyday life, here we ask whether it is conceptually possible for false approximations to qualify as knowledge. According to the factivity account, it is impossible to know false approximations, because knowledge requires truth. According to the representational adequacy account, it is possible to know false approximations, if they are close enough to the (...) truth for present purposes. In this paper, we adopt an experimental methodology to begin testing these two theories. When an agent provides a false and practically inadequate answer, both theories predict that people will deny knowledge. But the theories disagree about an agent who provides a false but practically adequate answer: the factivity hypothesis again predicts knowledge denial, whereas the representational adequacy hypothesis predicts knowledge attribution. Across two experiments, our principal finding was that people tended to attribute knowledge for false but practically adequate answers, which supports the representational adequacy account. We propose an interpretation of existing findings that preserves a conceptual link between knowledge and truth. According to this proposal, truth is not necessary for knowledge, but it is a feature of prototypical knowledge. (shrink)

Jennifer Hornsby has defended the Reasons-Knowledge Thesis : the claim that \-ing because p requires knowing that p, where the ‘because’ at issue is a rationalising ‘because’. She defends by appeal to the thought that it provides the best explanation of why the subject in a certain sort of Gettier case fails to be in a position to \ because p. Dustin Locke and, separately, Nick Hughes, present some modified barn-façade cases which seem to constitute counterexamples to and undermine (...) Hornsby’s way of motivating it by rendering their alternative Reasons-Explanation Thesis a better explanation of Hornsby’s datum. This paper defends and Hornsby’s argument for it against those objections. First, I point out that their supposedly intuitive verdict about the relevant barn-façade cases is not as intuitive as they think. Second, I point out that even if we share the intuition: we have strong reason to doubt the verdict anyway. And finally, I point out that since is independently implausible, the two problems can be tackled anyway. (shrink)

In this paper, I analyze the role of phenomenal knowledge in understanding the experiences of the victims of hermeneutical injustice. In particular, I argue that understanding that is enriched by phenomenal knowledge is a powerful tool to mitigate hermeneutical injustice. I proceed as follows: Firstly, I investigate the requirements for a full understanding of the experiences at the center of hermeneutical injustice and I argue that phenomenal knowledge is key to full understanding. Secondly, I distinguish between direct (...) phenomenal knowledge and imaginative phenomenal knowledge. Thirdly, I investigate whether one can gain imaginative phenomenal knowledge of the experiences of members of social groups other than one´s own. I consider reasons for pessimism in this regard and show that they are not conclusive. Then, I provide a model of how outgroup members can acquire imaginative knowledge of the experiences of the victims of hermeneutical injustice. Finally, I connect the varieties of phenomenal knowledge with different grades of understanding an experience and I outline how understanding that involves imaginative phenomenal knowledge helps to overcome various forms of hermeneutical injustice. (shrink)

Many have urged that the biggest obstacles to a physicalistic understanding of consciousness are the problems raised in connection with the subjectivity of consciousness. These problems are most acutely expressed in consideration of the knowledge argument against physicalism. I develop a novel account of the subjectivity of consciousness by explicating the ways in which mental representations may be perspectival. Crucial features of my account involve analogies between the representations involved in sensory experience and the ways in which pictorial representations (...) exhibit perspectives or points of view. I argue that the resultant account of subjectivity provides a basis for the strongest response physicalists can give to the knowledge argument. (shrink)

In IVP50S, Spinoza claims that “one who is moved to aid others neither by reason nor by pity is rightly called inhuman. For (by IIIP27) he seems to be unlike a man” (IVP50S). At first blush, the claim seems implausible, as it relies on the dubious assumption that beings will necessarily imitate the affects of conspecifics. In the first two sections of this paper, I explain why Spinoza accepts this thesis and show how this claim can be made compatible with (...) his account of representation. In the third and final section I offer an auxiliary defense of the thesis, showing that, according to Spinoza, to be human is to sociable, and sociability depends on the imitation of the affects. (shrink)

In the management of biomedical data, vocabularies such as ontologies and terminologies (O/Ts) are used for (i) domain knowledge representation and (ii) interoperability. The knowledge representation role supports the automated reasoning on, and analysis of, data annotated with O/Ts. At an interoperability level, the use of a communal vocabulary standard for a particular domain is essential for large data repositories and information management systems to communicate consistently with one other. Consequently, the interoperability benefit of selecting (...) a particular O/T as a standard for data exchange purposes is often seen by the end-user as a function of the number of applications using that vocabulary (and, by extension, the size of the user base). Furthermore, the adoption of an O/T as an interoperability standard requires confidence in its stability and guaranteed continuity as a resource. (shrink)