In this paper, we provide a semantics for a range of positive substructural logics, including both logics with and logics without modal connectives. The semantics is novel insofar as it is meant to explicitly capture the computational flavor of these logics, and to do so in a way that builds in both nondeterministic and nonconcurrent computational processes.

Turner argues that computer programs must have purposes, that implementation is not a kind of semantics, and that computers might need to understand what they do. I respectfully disagree: Computer programs need not have purposes, implementation is a kind of semantic interpretation, and neither human computers nor computing machines need to understand what they do.

There is a prevalent notion among cognitive scientists and philosophers of mind that computers are merely formal symbol manipulators, performing the actions they do solely on the basis of the syntactic properties of the symbols they manipulate. This view of computers has allowed some philosophers to divorce semantics from computational explanations. Semantic content, then, becomes something one adds to computational explanations to get psychological explanations. Other philosophers, such as Stephen Stich, have taken a stronger view, advocating doing (...) away with semantics entirely. This paper argues that a correct account of computation requires us to attribute content to computational processes in order to explain which functions are being computed. This entails that computational psychology must countenance mental representations. Since anti-semantic positions are incompatible with computational psychology thus construed, they ought to be rejected. Lastly, I argue that in an important sense, computers are not formal symbol manipulators. (shrink)

This essay considers what it means to understand natural language and whether a computer running an artificial-intelligence program designed to understand natural language does in fact do so. It is argued that a certain kind of semantics is needed to understand natural language, that this kind of semantics is mere symbol manipulation (i.e., syntax), and that, hence, it is available to AI systems. Recent arguments by Searle and Dretske to the effect that computers cannot understand natural language are (...) discussed, and a prototype natural-language-understanding system is presented as an illustration. (shrink)

In this paper, I show how semantic factors constrain the understanding of the computational phenomena to be explained so that they help build better mechanistic models. In particular, understanding what cognitive systems may refer to is important in building better models of cognitive processes. For that purpose, a recent study of some phenomena in rats that are capable of ‘entertaining’ future paths (Pfeiffer and Foster 2013) is analyzed. The case shows that the mechanistic account of physical computation may be (...) complemented with semantic considerations, and in many cases, it actually should. (shrink)

John Searle once said: "The Chinese room shows what we knew all along: syntax by itself is not sufficient for semantics. (Does anyone actually deny this point, I mean straight out? Is anyone actually willing to say, straight out, that they think that syntax, in the sense of formal symbols, is really the same as semantic content, in the sense of meanings, thought contents, understanding, etc.?)." I say: "Yes". Stuart C. Shapiro has said: "Does that make any sense? Yes: (...) Everything makes sense. The question is: What sense does it make?" This essay explores what sense it makes to say that syntax by itself is sufficient for semantics. (shrink)

http://www.diva-portal.org/mdh/theses/abstract.xsql?dbid=153.

Philosophical questions about minds and computation need to focus squarely on the mathematical theory of Turing machines (TM's). Surrogate TM's such as computers or formal systems lack abilities that make Turing machines promising candidates for possessors of minds. Computers are only universal Turing machines (UTM's)—a conspicuous but unrepresentative subclass of TM. Formal systems are only static TM's, which do not receive inputs from external sources. The theory of TM computation clearly exposes the failings of two prominent critiques, Searle's Chinese room (...) (1980) and arguments from Gödel's Incompleteness theorems (e.g., Lucas, 1961; Penrose, 1989), both of which fall short of addressing the complete TM model. Both UTM-computers and formal systems provide an unsound basis for debate. In particular, their special natures easily foster the misconception that computation entails intrinsically meaningless symbol manipulation. This common view is incorrect with respect to full-fledged TM's, which can process inputs non-formally, i.e., in a subjective and dynamically evolving fashion. To avoid a distorted understanding of the theory of computation, philosophical judgments and discussions should be grounded firmly upon the complete Turing machine model, the proper model for real computers. (shrink)

Contemporary philosophy and theoretical psychology are dominated by an acceptance of content-externalism: the view that the contents of one's mental states are constitutively, as opposed to causally, dependent on facts about the external world. In the present work, it is shown that content-externalism involves a failure to distinguish between semantics and pre-semantics---between, on the one hand, the literal meanings of expressions and, on the other hand, the information that one must exploit in order to ascertain their literal meanings. (...) It is further shown that, given the falsity of content-externalism, the falsity of the Computational Theory of Mind (CTM) follows. It is also shown that CTM involves a misunderstanding of terms such as "computation," "syntax," "algorithm," and "formal truth." Novel analyses of the concepts expressed by these terms are put forth. These analyses yield clear, intuition-friendly, and extensionally correct answers to the questions "what are propositions?, "what is it for a proposition to be true?", and "what are the logical and psychological differences between conceptual (propositional) and non-conceptual (non-propositional) content?" Naively taking literal meaning to be in lockstep with cognitive content, Burge, Salmon, Falvey, and other semantic externalists have wrongly taken Kripke's correct semantic views to justify drastic and otherwise contraindicated revisions of commonsense. (Salmon: What is non-existent exists; at a given time, one can rationally accept a proposition and its negation. Burge: Somebody who is having a thought may be psychologically indistinguishable from somebody who is thinking nothing. Falvey: somebody who rightly believes himself to be thinking about water is psychologically indistinguishable from somebody who wrongly thinks himself to be doing so and who, indeed, isn't thinking about anything.) Given a few truisms concerning the differences between thought-borne and sentence-borne information, the data is easily modeled without conceding any legitimacy to any one of these rationality-dismantling atrocities. (It thus turns out, ironically, that no one has done more to undermine Kripke's correct semantic points than Kripke's own followers!). (shrink)

The Computational Theory of Mind (CTM) holds that cognitive processes are essentially computational, and hence computation provides the scientific key to explaining mentality. The Representational Theory of Mind (RTM) holds that representational content is the key feature in distinguishing mental from non-mental systems. I argue that there is a deep incompatibility between these two theoretical frameworks, and that the acceptance of CTM provides strong grounds for rejecting RTM. The focal point of the incompatibility is the fact that representational (...) content is extrinsic to formal procedures as such, and the intended interpretation of syntax makes no difference to the execution of an algorithm. So the unique 'content' postulated by RTM is superfluous to the formal procedures of CTM. And once these procedures are implemented in a physical mechanism, it is exclusively the causal properties of the physical mechanism that are responsible for all aspects of the system's behaviour. So once again, postulated content is rendered superfluous. To the extent that semantic content may appear to play a role in behaviour, it must be syntactically encoded within the system, and just as in a standard computational artefact, so too with the human mind/brain - it's pure syntax all the way down to the level of physical implementation. Hence 'content' is at most a convenient meta-level gloss, projected from the outside by human theorists, which itself can play no role in cognitive processing. (shrink)

This essay describes computational semantic networks for a philosophical audience and surveys several approaches to semantic-network semantics. In particular, propositional semantic networks are discussed; it is argued that only a fully intensional, Meinongian semantics is appropriate for them; and several Meinongian systems are presented.

Estimating word complexity is a well-established task in computer-assisted language learning. So far, however, complexity estimation has been largely limited to comprehension. This neglects words that are easy to comprehend, but hard to produce. We introduce semantic error prediction (SEP) as a novel task that assesses the production complexity of content words. Given the corrected version of a learner-produced text, a system has to predict which content words replace tokens from the original text. We present and analyse one example of (...) such a semantic error prediction dataset, which we generate from an error correction dataset. As neural baselines, we use BERT, RoBERTa, and LLAMA2 embeddings for SEP. We show that our models can already improve downstream applications, such as predicting essay vocabulary scores. (shrink)

This paper argues that the idea of a computer is unique. Calculators and analog computers are not different ideas about computers, and nature does not compute by itself. Computers, once clearly defined in all their terms and mechanisms, rather than enumerated by behavioral examples, can be more than instrumental tools in science, and more than source of analogies and taxonomies in philosophy. They can help us understand semantic content and its relation to form. This can be achieved because they have (...) the potential to do more than calculators, which are computers that are designed not to learn. Today’s computers are not designed to learn; rather, they are designed to support learning; therefore, any theory of content tested by computers that currently exist must be of an empirical, rather than a formal nature. If they are designed someday to learn, we will see a change in roles, requiring an empirical theory about the Turing architecture’s content, using the primitives of learning machines. This way of thinking, which I call the intensional view of computers, avoids the problems of analogies between minds and computers. It focuses on the constitutive properties of computers, such as showing clearly how they can help us avoid the infinite regress in interpretation, and how we can clarify the terms of the suggested mechanisms to facilitate a useful debate. Within the intensional view, syntax and content in the context of computers become two ends of physically realizing correspondence problems in various domains. (shrink)

Semantic information is usually supposed to satisfy the veridicality thesis: p qualifies as semantic information only if p is true. However, what it means for semantic information to be true is often left implicit, with correspondentist interpretations representing the most popular, default option. The article develops an alternative approach, namely a correctness theory of truth (CTT) for semantic information. This is meant as a contribution not only to the philosophy of information but also to the philosophical debate on the nature (...) of truth. After the introduction, in Sect. 2, semantic information is shown to be translatable into propositional semantic information (i). In Sect. 3, i is polarised into a query (Q) and a result (R), qualified by a specific context, a level of abstraction and a purpose. This polarization is normalised in Sect. 4, where [Q + R] is transformed into a Boolean question and its relative yes/no answer [Q + A]. This completes the reduction of the truth of i to the correctness of A. In Sects. 5 and 6, it is argued that (1) A is the correct answer to Q if and only if (2) A correctly saturates Q by verifying and validating it (in the computer science’s sense of verification and validation ); that (2) is the case if and only if (3) [Q + A] generates an adequate model (m) of the relevant system (s) identified by Q; that (3) is the case if and only if (4) m is a proxy of s (in the computer science’s sense of proxy ) and (5) proximal access to m commutes with the distal access to s (in the category theory’s sense of commutation ); and that (5) is the case if and only if (6) reading/writing (accessing, in the computer science’s technical sense of the term) m enables one to read/write (access) s. Sect. 7 provides some further clarifications about CTT, in the light of semantic paradoxes. Section 8 draws a general conclusion about the nature of CTT as a theory for systems designers not just systems users. In the course of the article all technical expressions from computer science are explained. (shrink)

Is the mathematical function being computed by a given physical system determined by the system’s dynamics? This question is at the heart of the indeterminacy of computation phenomenon (Fresco et al. [unpublished]). A paradigmatic example is a conventional electrical AND-gate that is often said to compute conjunction, but it can just as well be used to compute disjunction. Despite the pervasiveness of this phenomenon in physical computational systems, it has been discussed in the philosophical literature only indirectly, mostly with (...) reference to the debate over realism about physical computation and computationalism. A welcome exception is Dewhurst’s ([2018]) recent analysis of computational individuation under the mechanistic framework. He rejects the idea of appealing to semantic properties for determining the computational identity of a physical system. But Dewhurst seems to be too quick to pay the price of giving up the notion of computational equivalence. We aim to show that the mechanist need not pay this price. The mechanistic framework can, in principle, preserve the idea of computational equivalence even between two different enough kinds of physical systems, say, electrical and hydraulic ones. (shrink)

European Computing and Philosophy conference, 2–4 July Barcelona The Seventh ECAP (European Computing and Philosophy) conference was organized by Jordi Vallverdu at Autonomous University of Barcelona. The conference started with the IACAP (The International Association for CAP) presidential address by Luciano Floridi, focusing on mechanisms of knowledge production in informational networks. The first keynote delivered by Klaus Mainzer made a frame for the rest of the conference, by elucidating the fundamental role of complexity of informational structures that can be analyzed (...) on different levels of organization giving place for variety of possible approaches which converge in this cross-disciplinary and multi-disciplinary research field. Keynotes by Kevin Warwick about re-embodiment of rats’ neurons into robots, Raymond Turner on syntax and semantics in programming languages, Roderic Guigo on Biocomputing Sciences and Francesco Subirada on the past and future of supercomputing presented different topics of philosophical as well as practical aspects of computing. Vonference tracks included: Philosophy of Information (Patrick Allo), Philosophy of Computer Science (Raymond Turner), Computer and Information Ethics (Johnny Søraker and Alison Adam), Computational Approaches to the Mind (Ruth Hagengruber), IT and Cultural Diversity (Jutta Weber and Charles Ess), Crossroads (David Casacuberta), Robotics, AI & Ambient Intelligence (Thomas Roth-Berghofer), Biocomputing, Evolutionary and Complex Systems (Gordana Dodig Crnkovic and Søren Brier), E-learning, E-science and Computer-Supported Cooperative Work (Annamaria Carusi) and Technological Singularity and Acceleration Studies (Amnon Eden). (shrink)

The epistemic modal auxiliaries must and might are vehicles for expressing the force with which a proposition follows from some body of evidence or information. Standard approaches model these operators using quantificational modal logic, but probabilistic approaches are becoming increasingly influential. According to a traditional view, must is a maximally strong epistemic operator and might is a bare possibility one. A competing account—popular amongst proponents of a probabilisitic turn—says that, given a body of evidence, must \ entails that \\) is (...) high but non-maximal and might \ that \\) is significantly greater than 0. Drawing on several observations concerning the behavior of must, might and similar epistemic operators in evidential contexts, deductive inferences, downplaying and retractions scenarios, and expressions of epistemic tension, I argue that those two influential accounts have systematic descriptive shortcomings. To better make sense of their complex behavior, I propose instead a broadly Kratzerian account according to which must \ entails that \ = 1\) and might \ that \ > 0\), given a body of evidence and a set of normality assumptions about the world. From this perspective, must and might are vehicles for expressing a common mode of reasoning whereby we draw inferences from specific bits of evidence against a rich set of background assumptions—some of which we represent as defeasible—which capture our general expectations about the world. I will show that the predictions of this Kratzerian account can be substantially refined once it is combined with a specific yet independently motivated ‘grammatical’ approach to the computation of scalar implicatures. Finally, I discuss some implications of these results for more general discussions concerning the empirical and theoretical motivation to adopt a probabilisitic semantic framework. (shrink)

I review a widely accepted argument to the conclusion that the contents of our beliefs, desires and other mental states cannot be causally efficacious in a classical computational model of the mind. I reply that this argument rests essentially on an assumption about the nature of neural structure that we have no good scientific reason to accept. I conclude that computationalism is compatible with wide semantic causal efficacy, and suggest how the computational model might be modified to accommodate (...) this possibility. (shrink)

The article develops a correctness theory of truth (CTT) for semantic information. After the introduction, in section two, semantic information is shown to be translatable into propositional semantic information (i). In section three, i is polarised into a query (Q) and a result (R), qualified by a specific context, a level of abstraction and a purpose. This polarization is normalised in section four, where [Q + R] is transformed into a Boolean question and its relative yes/no answer [Q + A]. (...) This completes the reduction of the truth of i to the correctness of A. In sections five and six, it is argued that (1) A is the correct answer to Q if and only if (2) A correctly saturates (in a Fregean sense) Q by verifying and validating it (in the computer science’s sense of “verification” and “validation”); that (2) is the case if and only if (3) [Q + A] generates an adequate model (m) of the relevant system (s) identified by Q; that (3) is the case if and only if (4) m is a proxy of s (in the computer science’s sense of “proxy”) and (5) proximal access to m commutes with the distal access to s (in the category theory’s sense of “commutation”); and that (5) is the case if and only if (6) reading/writing (accessing, in the computer science’s technical sense of the term) m enables one to read/write (access) s. The last section draws a general conclusion about the nature of CTT as a theory for systems designers not just systems users. (shrink)

In this paper, we present a formalism for handling polysemy in spatial expressions based on supervaluation semantics called standpoint semantics for polysemy (SSP). The goal of this formalism is, given a prepositional phrase, to define its possible spatial interpretations. For this, we propose to characterize spatial prepositions by means of a triplet ⟨ image schema, semantic feature, spatial axis⟩⁠. The core of SSP is predicate grounding theories, which are formulas of a first-order language that define a spatial preposition (...) through the semantic features of its trajector and landmark. Precisifications are also established, which are a set of formulae of a qualitative spatial reasoning formalism that aims to provide the spatial characterization of the trajector with respect to the landmark. In addition to the theoretical model, we also present results of a computational implementation of SSP for the preposition ‘in’. (shrink)

According to Conceptual Role Semantics, the meaning of a representation is the role of that representation in the cognitive life of the agent, e.g. in perception, thought and decision-making. It is an extension of the well known "use" theory of meaning, according to which the meaning of a word is its use in communication and more generally, in social interaction. CRS supplements external use by including the role of a symbol inside a computer or a brain. The uses appealed (...) to are not just actual, but also counterfactual: not only what effects a thought does have, but what effects it would have had if stimuli or other states had differed. The view has arisen separately in philosophy and in cognitive science. The source of the view is Wittgenstein and Sellars, but the source in contemporary philosophy is a series of papers by Harman and Field. Other proponents in philosophy have included Block, Horwich, Loar, McGinn and Peacocke. In cognitive science, they include Woods and Miller and Johnson-Laird. (shrink)

The prelims comprise: Introduction: Two Semantic Projects History The Uses of Semantics Conclusions.

This article offers an explanation of perhaps Wittgenstein’s strangest and least intuitive thesis – the semantical mutation thesis – according to which one can never answer a mathematical conjecture because the new proof alters the very meanings of the terms involved in the original question. Instead of basing our justification on the distinction between mere calculation and proofs of isolated propositions, characteristic of Wittgenstein’s intermediary period, we generalize it to include conjectures involving effective procedures as well.

The paper presents a paradoxical feature of computational systems that suggests that computationalism cannot explain symbol grounding. If the mind is a digital computer, as computationalism claims, then it can be computing either over meaningful symbols or over meaningless symbols. If it is computing over meaningful symbols its functioning presupposes the existence of meaningful symbols in the system, i.e. it implies semantic nativism. If the mind is computing over meaningless symbols, no intentional cognitive processes are available prior to symbol (...) grounding. In this case, no symbol grounding could take place since any grounding presupposes intentional cognitive processes. So, whether computing in the mind is over meaningless or over meaningful symbols, computationalism implies semantic nativism. (shrink)

The starting point for this paper is a critical discussion of claims of psychological reality articulated within Borg’s (forth.) minimal semantics and Carpintero’s (2007) character*-semantics. It has been proposed, for independent reasons, that their respective accounts can accommodate, or at least avoid the challenge from psychological evidence. I outline their respective motivations, suggesting various shortcomings in their efforts of preserving the virtues of an uncontaminated semantics in the face of psychological objection (I-II), and try to make the (...) case that, at least for a theory of utterance comprehension, a truth-conditional pragmatic stance is far preferable. An alternative from a relevance-theoretic perspective is offered in terms of mutual adjustment between truth-conditional content and implicature(s), arguing that many “free” pragmatic processes are needed to uncover the truth-conditional content, which can then warrant the expected implicature(s) (III). I finally illustrate the difficulties their accounts have in predicting the correct order of interpretation in cases of ironic metaphor, i.e. metaphor is computed first, as part of truth-conditional content, while irony is inferentially grounded in metaphorical content (IV). (shrink)

Semantic interoperability can be defined as the ability of two or more computer systems to exchange information in such a way that the meaning of that information can be automatically interpreted by the receiving system accurately enough to produce useful results to the end users of both systems. Several activities are currently being performed by a variety of stakeholders to achieve semantic interoperability in healthcare. Many of these activities are not beneficial, because they place too great a focus on business (...) aspects and not enough on involvement of the right sorts of researchers, in particular those that are able to see how the data and information relate to the entities of concern on the side of the patient. The lack of a central focus on the patient, and the associated focus on ‘concepts’, have spawned a variety of mutually incompatible terminologies exhibiting non-resolvable overlap. The predominance of the healthcare IT industry in the writing and selection of semantic interoperability standards mitigates against the benefits that standards, when well designed, can bring about. (shrink)

We start with the ambition -- dating back to the early days of the semantic web -- of assembling a significant portion human knowledge into a contradiction-free form using semantic web technology. We argue that this would not be desirable, because there are concepts, known as essentially contested concepts, whose definitions are contentious due to deep-seated ethical disagreements. Further, we argue that the ninetenth century hermeneutical tradition has a great deal to say, both about the ambition, and about why it (...) fails. We conclude with some remarks about statistics. (shrink)

Virtual environments engage millions of people and billions of dollars each year. What is the ontological status of the virtual objects that populate those environments? An adequate answer to that question requires a developed semantics for virtual environments. The truth-conditions must be identified for “tree”-sentences when uttered by speakers immersed in a virtual environment (VE). It will be argued that statements about virtual objects have truth-conditions roughly comparable to the verificationist conditions popular amongst some contemporary antirealists. This does not (...) mean that the virtual objects lack ontological standing. There is an important sense in which virtual objects are no less real for being mind-dependent. (shrink)

What is the computational notion of “implementation”? It is not individuation, instantiation, reduction, or supervenience. It is, I suggest, semantic interpretation.

The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open (...) Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers. (shrink)

Human creativity generates novel ideas to solve real-world problems. This thereby grants us the power to transform the surrounding world and extend our human attributes beyond what is currently possible. Creative ideas are not just new and unexpected, but are also successful in providing solutions that are useful, efficient and valuable. Thus, creativity optimizes the use of available resources and increases wealth. The origin of human creativity, however, is poorly understood, and semantic measures that could predict the success of generated (...) ideas are currently unknown. Here, we analyze a dataset of design problem-solving conversations in real-world settings by using 49 semantic measures based on WordNet 3.1 and demonstrate that a divergence of semantic similarity, an increased information content, and a decreased polysemy predict the success of generated ideas. The first feedback from clients also enhances information content and leads to a divergence of successful ideas in creative problem solving. These results advance cognitive science by identifying real-world processes in human problem solving that are relevant to the success of produced solutions and provide tools for real-time monitoring of problem solving, student training and skill acquisition. A selected subset of information content (IC Sánchez–Batet) and semantic similarity (Lin/Sánchez–Batet) measures, which are both statistically powerful and computationally fast, could support the development of technologies for computer-assisted enhancements of human creativity or for the implementation of creativity in machines endowed with general artificial intelligence. (shrink)

ABSTRACT -/- A propositional attitude (PA) is a belief, desire, fear, etc., that x is the case. This dissertation addresses the question of the semantic content of a specific kind of PA-instance: an instance of a belief of the form all Fs are Gs. The belief that all bachelors are sports fans has this form, while the belief that Spain is a country in Eastern Europe do not. Unlike a state of viewing the color of an orange, a belief-instance is (...) semantically contentful because it has reference, a meaning, logical implications, or a truth-value. While the intrinsic semantics view holds that either concepts or abstract objects are the source of content for PAs, the extrinsic semantics view holds that symbols of a mental language provide this content. I argue that a successful theory of intentionality must explain: (1) the truth-preserving causal powers of PAs, (2) the failure of the deductive principle Substitutivity to preserve truth over sentences that ascribe PAs, and (3) the truth-evaluability of PAs. As an internalist version of the extrinsic semantics view, I first evaluate Fodor’s Computational Theory of Mind, which says the semantic ingredients of mental states are symbols governed by rules of a mental syntax. I argue that in order to meet (1), CTM would have to associate the causal patterns of each thought-type with the inferential relations of some proposition – in an arbitrary or question-begging way. I also evaluate Fodor’s causal theory, as an externalist version of the extrinsic semantics view. This view is that lawlike causal relations between mental symbols and objects determine the reference, and thus the truth-value, of a thought. I argue that Brian Loar’s circularity objection refutes the ability of this theory to meet (3); and I endorse the intrinsic semantics perspective. I evaluate Frege’s theory of abstract, mind-external, and intrinsically semantic objects (senses), as an attempt to meet condition (2). I conclude that mind-external universals are the source of the intrinsically semantic features of concepts. Finally, I put forth a theory called ‘Bare Property Intentionality’, which describes the features of intrinsically representative and semantic concepts that connect them to these universals. (shrink)

The purpose of this essay is to study the extent in which the semantics for different logical systems can be represented game theoretically. I will begin by considering different definitions of what it means to gamify a semantics, and show completeness and limitative results. In particular, I will argue that under a proper definition of gamification, all finitely algebraizable logics can be gamified, as well as some infinitely algebraizable ones (like Łukasiewicz) and some non-algebraizable (like intuitionistic and van (...) Fraassen supervaluation logic). (shrink)

In this paper, the role of the environment and physical embodiment of computational systems for explanatory purposes will be analyzed. In particular, the focus will be on cognitive computational systems, understood in terms of mechanisms that manipulate semantic information. It will be argued that the role of the environment has long been appreciated, in particular in the work of Herbert A. Simon, which has inspired the mechanistic view on explanation. From Simon’s perspective, the embodied view on cognition seems (...) natural but it is nowhere near as critical as its proponents suggest. The only point of difference between Simon and embodied cognition is the significance of body-based off-line cognition; however, it will be argued that it is notoriously over-appreciated in the current debate. The new mechanistic view on explanation suggests that even if it is critical to situate a mechanism in its environment and study its physical composition, or realization, it is also stressed that not all detail counts, and that some bodily features of cognitive systems should be left out from explanations. (shrink)

Both in formal and computational natural language semantics, the classical correspondence view of meaning – and, more specifically, the view that the meaning of a declarative sentence coincides with its truth conditions – is widely held. Truth (in the world or a situation) plays the role of the given, and meaning is analysed in terms of it. Both language and the world feature in this perspective on meaning, but language users are conspicuously absent. In contrast, the inferentialist (...) class='Hi'>semantics that Robert Brandom proposes in his magisterial book ‘Making It Explicit’ puts the language user centre stage. According to his theory of meaning, the utterance of a sentence is meaningful in as far as it is a move by a language user in a game of giving and asking for reasons (with reasons underwritten by a notion of good inferences). In this paper, I propose a proof-theoretic formalisation of the game of giving and asking for reasons that lends itself to computer implementation. In the current proposal, I flesh out an account of defeasible inferences, a variety of inferences which play a pivotal role in ordinary (and scientific) language use. (shrink)

The paper shows how ideas that explain the sense of an expression as a method or algorithm for finding its reference, preshadowed in Frege’s dictum that sense is the way in which a referent is given, can be formalized on the basis of the ideas in Thomason (1980). To this end, the function that sends propositions to truth values or sets of possible worlds in Thomason (1980) must be replaced by a relation and the meaning postulates governing the behaviour of (...) this relation must be given in the form of a logic program. The resulting system does not only throw light on the properties of sense and their relation to computation, but also shows circular behaviour if some ingredients of the Liar Paradox are added. The connection is natural, as algorithms can be inherently circular and the Liar is explained as expressing one of those. Many ideas in the present paper are closely related to those in Moschovakis (1994), but receive a considerably lighter formalization. (shrink)

The paper develops some of the conclusions, reached in Floridi (2007), concerning the future developments of Information and Communication Technologies (ICTs) and their impact on our lives. The two main theses supported in that article were that, as the information society develops, the threshold between online and offline is becoming increasingly blurred, and that once there won't be any significant difference, we shall gradually re-conceptualise ourselves not as cyborgs but rather as inforgs, i.e. socially connected, informational organisms. In this paper, (...) I look at the development of the so-called Semantic Web and Web 2.0 from this perspective and try to forecast their future. Regarding the Semantic Web, I argue that it is a clear and well-defined project, which, despite some authoritative views to the contrary, is not a promising reality and will probably fail in the same way AI has failed in the past. Regarding Web 2.0, I argue that, although it is a rather ill-defined project, which lacks a clear explanation of its nature and scope, it does have the potentiality of becoming a success (and indeed it is already, as part of the new phenomenon of Cloud Computing) because it leverages the only semantic engines available so far in nature, us. I conclude by suggesting what other changes might be expected in the future of our digital environment. (shrink)

The paper briefly surveys the sentential proof-theoretic semantics for fragment of English. Then, appealing to a version of Frege’s context-principle (specified to fit type-logical grammar), a method is presented for deriving proof-theoretic meanings for sub-sentential phrases, down to lexical units (words). The sentential meaning is decomposed according to the function-argument structure as determined by the type-logical grammar. In doing so, the paper presents a novel proof-theoretic interpretation of simple type, replacing Montague’s model-theoretic type interpretation (in arbitrary Henkin models). The (...) domains of derivations are collections of derivations in the associated “dedicated” natural-deduction proof-system, and functions therein (with no appeal to models, truth-values and elements of a domain). The compositionality of the semantics is analyzed. (shrink)

A computer can come to understand natural language the same way Helen Keller did: by using “syntactic semantics”—a theory of how syntax can suffice for semantics, i.e., how semantics for natural language can be provided by means of computational symbol manipulation. This essay considers real-life approximations of Chinese Rooms, focusing on Helen Keller’s experiences growing up deaf and blind, locked in a sort of Chinese Room yet learning how to communicate with the outside world. Using the (...) SNePS computational knowledge-representation system, the essay analyzes Keller’s belief that learning that “everything has a name” was the key to her success, enabling her to “partition” her mental concepts into mental representations of: words, objects, and the naming relations between them. It next looks at Herbert Terrace’s theory of naming, which is akin to Keller’s, and which only humans are supposed to be capable of. The essay suggests that computers at least, and perhaps non-human primates, are also capable of this kind of naming. (shrink)

The History of Ideas is presently enjoying a certain renaissance after a long period of disrepute. Increasing quantities of digitally available historical texts and the availability of computational tools for the exploration of such masses of sources, it is suggested, can be of invaluable help to historians of ideas. The question is: how exactly? In this paper, we argue that a computational history of ideas is possible if the following two conditions are satisfied: (i) Sound Method . A (...) computational history of ideas must be built upon a sound theoretical foundation for its methodology, and the only such foundation is given by the use of models , i.e., fully explicit and revisable interpretive frameworks or networks of concepts developed by the historians of ideas themselves. (ii) Data Organisation. Interpretive models in our sense must be seen as topic-specific knowledge organisation systems (KOS) implementable (i.e. formalisable) as e.g. computer science ontologies. We thus require historians of ideas to provide explicitly structured semantic framing of domain knowledge before investigating texts computationally, and to constantly re-input findings from the interpretive point of view. In this way, a computational history of ideas maximally profits from computer methods while also keeping humanities experts in the loop. We elucidate our proposal with reference to a model of the notion of axiomatic science in 18th -19th century Europe. (shrink)

“Morphological computation” is an increasingly important concept in robotics, artificial intelligence, and philosophy of the mind. It is used to understand how the body contributes to cognition and control of behavior. Its understanding in terms of "offloading" computation from the brain to the body has been criticized as misleading, and it has been suggested that the use of the concept conflates three classes of distinct processes. In fact, these criticisms implicitly hang on accepting a semantic definition of what constitutes computation. (...) Here, I argue that an alternative, mechanistic view on computation offers a significantly different understanding of what morphological computation is. These theoretical considerations are then used to analyze the existing research program in developmental biology, which understands morphogenesis, the process of development of shape in biological systems, as a computational process. This important line of research shows that cognition and intelligence can be found across all scales of life, as the proponents of the basal cognition research program propose. Hence, clarifying the connection between morphological computation and morphogenesis allows for strengthening the role of the former concept in this emerging research field. (shrink)

Objective. Conceptualization of the definition of space as a semantic unit of language consciousness. -/- Materials & Methods. A structural-ontological approach is used in the work, the methodology of which has been tested and applied in order to analyze the subject matter area of psychology, psycholinguistics and other social sciences, as well as in interdisciplinary studies of complex systems. Mathematical representations of space as a set of parallel series of events (Alexandrov) were used as the initial theoretical basis of the (...) structural-ontological analysis. In this case, understanding of an event was considered in the context of the definition adopted in computer science – a change in the object properties registered by the observer. -/- Results. The negative nature of space realizes itself in the subject-object structure, the components interaction of which is characterized by a change – a key property of the system under study. Observer’s registration of changes is accompanied by spatial focusing (situational concretization of the field of changes) and relating of its results with the field of potentially distinguishable changes (subjective knowledge about «changing world»). The indicated correlation performs the function of space identification in terms of recognizing its properties and their subjective significance, depending on the features of the observer`s motivational sphere. As a result, the correction of the actual affective dynamics of the observer is carried out, which structures the current perception of space according to principle of the semantic fractal. Fractalization is a formation of such a subjective perception of space, which supposes the establishment of semantic accordance between the situational field of changes, on the one hand, and the worldview, as well as the motivational characteristics of the observer, on the other. -/- Conclusions. Performed structural-ontological analysis of the system formed by the interaction of the perceptual function of the psyche and the semantic field of the language made it possible to conceptualize the space as a field of changes potentially distinguishable by the observer, structurally organized according to the principle of the semantic fractal. The compositional features of the fractalization process consist in fact that the semantic fractal of space is relevant to the product of the difference between the situational field of changes and the field of potentially distinguishable changes, adjusted by the current configuration of the observer`s value-needs hierarchy and reduced by his actual affective dynamics. (shrink)

In this paper it is argued that the conjunction of linguistic ersatzism, the ontologically deflationary view that possible worlds are maximal and consistent sets of sentences, and possible world semantics, the view that the meaning of a sentence is the set of possible worlds at which it is true, implies that no actual speaker can effectively use virtually any language to successfully communicate information. This result is based on complexity issues that relate to our finite computational ability to (...) deal with large bodies of information and a strong, but well motivated, assumption about the cognitive accessibility of meanings of sentences ersatzers seem to be implicitly committed to. It follows that linguistic ersatzism, possible world semantics, or both must be rejected. (shrink)

In this reply to James H. Fetzer’s “Minds and Machines: Limits to Simulations of Thought and Action”, I argue that computationalism should not be the view that (human) cognition is computation, but that it should be the view that cognition (simpliciter) is computable. It follows that computationalism can be true even if (human) cognition is not the result of computations in the brain. I also argue that, if semiotic systems are systems that interpret signs, then both humans and computers are (...) semiotic systems. Finally, I suggest that minds can be considered as virtual machines implemented in certain semiotic systems, primarily the brain, but also AI computers. In doing so, I take issue with Fetzer’s arguments to the contrary. (shrink)

Logics based on weak Kleene algebra (WKA) and related structures have been recently proposed as a tool for reasoning about flaws in computer programs. The key element of this proposal is the presence, in WKA and related structures, of a non-classical truth-value that is “contaminating” in the sense that whenever the value is assigned to a formula ϕ, any complex formula in which ϕ appears is assigned that value as well. Under such interpretations, the contaminating states represent occurrences of a (...) flaw. However, since different programs and machines can interact with (or be nested into) one another, we need to account for different kind of errors, and this calls for an evaluation of systems with multiple contaminating values. In this paper, we make steps toward these evaluation systems by considering two logics, HYB1 and HYB2, whose semantic interpretations account for two contaminating values beside classical values 0 and 1. In particular, we provide two main formal contributions. First, we give a characterization of their relations of (multiple-conclusion) logical consequence—that is, necessary and sufficient conditions for a set Δ of formulas to logically follow from a set Γ of formulas in HYB1 or HYB2 . Second, we provide sound and complete sequent calculi for the two logics. (shrink)

In this paper, I revisit Frege's theory of sense and reference in the constructive setting of the meaning explanations of type theory, extending and sharpening a program–value analysis of sense and reference proposed by Martin-Löf building on previous work of Dummett. I propose a computational identity criterion for senses and argue that it validates what I see as the most plausible interpretation of Frege's equipollence principle for both sentences and singular terms. Before doing so, I examine Frege's implementation of (...) his theory of sense and reference in the logical framework of Grundgesetze, his doctrine of truth values, and views on sameness of sense as equipollence of assertions. (shrink)

: The Hamblin-Karttunen approach has led to many insights about questions in English. In this article the results of this rule-by-rule tradition are reconsidered from a crosslinguistic perspective. Starting from the type-driven XLS theory developed in Bittner (1994a, b), it is argued that evidence from simple questions (in English, Polish, Lakhota and Warlpiri) leads to certain revisions. The revised XLS theory then immediately generalizes to complex questions — including scope marking (Hindi), questions with quantifiers (English) and multiple wh-questions (English, Hindi, (...) Japanese). Eliminating language- and construction-specific information from the compositional rules, in favor of universal semantic filters, leads to analyses that not only generalize across unrelated languages but are also empirically more accurate, not less. (shrink)

An important part of the Unified Medical Language System (UMLS) is its Semantic Network, consisting of 134 Semantic Types connected to each other by edges formed by one or more of 54 distinct Relation Types. This Network is however for many purposes overcomplex, and various groups have thus made attempts at simplification. Here we take this work further by simplifying the relations which involve the three Semantic Types – Diagnostic Procedure, Laboratory Procedure and Therapeutic or Preventive Procedure. We define operators (...) which can be used to generate terms instantiating types from this selected set when applied to terms designating certain other Semantic Types, including almost all the terms specifying clinical tasks. Usage of such operators thus provides a useful and economical way of specifying clinical tasks. The operators allow us to define a mapping between those types within the UMLS which do not represent clinical tasks and those which do. This mapping then provides a basis for an ontology of clinical tasks that can be used in the formulation of computer-interpretable clinical guideline models. (shrink)

By creating certain marks on paper, or by making certain sounds-breathing past a moving tongue-or by articulation of hands and bodies, language users can give expression to their mental lives. With language we command, assert, query, emote, insult, and inspire. Language has meaning. This fact can be quite mystifying, yet a science of linguistic meaning-semantics-has emerged at the intersection of a variety of disciplines: philosophy, linguistics, computer science, and psychology. Semantics is the study of meaning. But what exactly (...) is "meaning"? What is the exact target of semantic theory? Much of the early work in natural language semantics was accompanied by extensive reflection on the aims of semantic theory, and the form a theory must take to meet those aims. But this meta-theoretical reflection has not kept pace with recent theoretical innovations. This volume re-addresses these questions concerning the foundations of natural language semantics in light of the current state-of-the-art in semantic theorising. (shrink)

This paper defends the view that the Faculty of Language is compositional, i.e., that it computes the meaning of complex expressions from the meanings of their immediate constituents and their structure. I fargue that compositionality and other competing constraints on the way in which the Faculty of Language computes the meanings of complex expressions should be understood as hypotheses about innate constraints of the Faculty of Language. I then argue that, unlike compositionality, most of the currently available non-compositional constraints predict (...) incorrect patterns of early linguistic development. This supports the view that the Faculty of Language is com- positional. More generally, this paper presents a way of framing the compositionality debate (by focusing on its implications for language acquisition) that can lead to its even- tual resolution, so it will hopefully also interest theorists who disagree with its main conclusion. (shrink)