A formal model of the processes of digestion in a hypothetical cell is developed and discussed as a case study of how the threefold logic of Peircean semiotics works within Rosen’s paradigm of relational ontology. The formal model is used to demonstrate several fundamental differences between a relational description of biological processes and a mechanistic description. The formal model produces a logic of embodied generalization that is mediated and determined by the cell through its interactions with the (...) environment. Specifically, the synchronization of the functions of pattern recognition and semantic attribution results in an open and adaptive learning system that is stabilized by a hermeneutical circle. The relational principles of biosemiotics demonstrated through this case study are applicable to other biological systems, as well as to the relational ontology of systems theory, artificial intelligence systems, and relativistic quantum theory. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players (...) to explore overlapping causal patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types in an intelligent (...) manner according to the behavior of the student. An evaluation of the intelligent tutoring system has revealed reasonably acceptable results in terms of its usability and learning abilities are concerned. (shrink)

In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types in an intelligent (...) manner according to the behavior of the student. An evaluation of the intelligent tutoring system has revealed reasonably acceptable results in terms of its usability and learning abilities are concerned. (shrink)

Complex constraints like conditionals ('If A, then B') and probabilistic constraints ('The probability that A is p') pose problems for Bayesian theories of learning. Since these propositions do not express constraints on outcomes, agents cannot simply conditionalize on the new information. Furthermore, a natural extension of conditionalization, relative information minimization, leads to many counterintuitive predictions, evidenced by the sundowners problem and the Judy Benjamin problem. Building on the notion of a `paradigm shift' and empirical research in psychology and economics, (...) I argue that the model of hypothesis testing can explain how people learn complex, theory-laden propositions like conditionals and probability constraints. Theories are formalized as probability distributions over a set of possible outcomes and theory change is triggered by a constraint which is incompatible with the initial theory. This leads agents to consult a higher order probability function, or a 'prior over priors,' to choose the most likely alternative theory which satisfies the constraint. The hypothesis testing model is applied to three examples: learning a simple probabilistic constraint involving coin bias, the sundowners problem for conditional learning, and the Judy Benjamin problem for learning conditional probability constraints. (shrink)

Many theories about the teaching of logic and critical thinking take for granted that theoretical learning, the learning of formal rules for example, and its practical application are sufficient to master the tools taught and to take the habit of using them. However, this way of teaching is not efficient, a conclusion supported by much work in cognitive science. Approaching cognition evolutionarily with dual-process theories allows for an explanation of these insufficiencies and offers clues on how we (...) could teach critical thinking and logic more efficiently. In this article, we want to present this approach and explore these leads in order to make some pedagogical recommendations and lay the foundations of a framework. We will put forward an example of the application of this research program with philosophy for children. (shrink)

There is no shortage of pedagogical theories from the tradition formal methods of instruction to the free-play methods of unschooling. A sharp shift in education and instruction models took place with the introduction of critical pedagogy. The focus was no longer on the authority of the teacher and the submissive, passive approach taken by the learner, but rather on the engagement between the two. Still, even when critical pedagogy is utilized in a formal model of education something is (...) missing from the system—experiential learning. Although the unschooling method has been criticized it does provide the benefit of experiential learning. This paper explores the nature of education and evaluates models and theories of pedagogy with the conclusion that a paradoxical approach in which there is a merger between the formal guidelines set by traditional educational models and the experiential learning methods of unschooling approach best prepares learners for the world and to be engaged citizens. Although what, precisely, this paradoxical system would entail is not discussed in this paper, it opens the door for further discussion on the topic and for consideration of the theories which have attempted to do exactly this and improve upon them going forward. (shrink)

The target of Second- Language Acquisition (SLA), emerged in the second half of the 20th century, was to be helpful in foreign- language education/ teaching. It denotes mostly the study of individuals (or sometimes groups) who are learning a language consequent to learning their first language when they are young children. At the same time, it signifies the process of learning a second language. The added language is named a second language, but it might indeed be the (...) third, fourth or more which is going to be acquired. The range of SLA comprises informal Second- Language Learning occurring in natural milieus, formal second- language learning occurring in classroom or the one that contains a combination of them both, that is, settings and conditions. The three main aspects for the study of SLA process are the linguistic, psychological and social aspects. The Monitor Theory/ Model postulated by Krashen in the 1970s is a psychological approach in nature. With its five hypotheses (The Acquisition– Learning Hypothesis, The Monitor Hypothesis, The Natural Order Hypothesis, The Input Hypothesis, and The Affective Filter Hypothesis), it tries to find answers to the problems of SLA, such as what does a second- language learner come to know, how the acquisition process takes place, and why some learners are more successful than others? The Monitor Theory (MT) received extensively many criticisms after its appearance and was rejected. Its teaching implications were also at the centre of criticisms. What place does MT occupy in SLA today? This study aims to try to find an answer. The other questions are: How important is the MT for SLA? What kind of criticisms are expressed against it? How fair is the criticism by McLaughlin (1978, 1987)? The working hypotheses of the present work are: The hypotheses developed by Krashen are not/ will not be rejected. Because science is still lying in the so- called agony phase, and cannot find any answers to all questions in psychology (e.g. how exactly is the processing of language; in particular and of mind in general). Moreover, the problems related to memory etc., the thoughts emanated from the MT can probably not be refuted. They have evolved so far and will be evolved further, perhaps with small differences. This research is completely based on the literature written since the time the theory was developed. In other words, it was carried out using a descriptive method without using a special data collection tool. The sources written on the subject were reviewed and an answer to the research questions was tried to be found. Even though the theory is expressed with different names and different meanings today, it has survived all the criticisms made, and it has been concluded that it still occupies an important place in the discipline of second- language acquisition (SLA) and foreign- language teaching. Again, the inquiries carried out since the 1970s delineate that the implications in favour of language education are not very different from those stated by Krashen (1982), which were the products of his opinions in that period. There are still basic consequences grounded on MT for language teaching today. (shrink)

Customer behavior, market dynamics, and technological advances have made it challenging for marketing theorists to provide comprehensive explanations and actionable insights. Although there are numerous substantive marketing frameworks, no formal marketing theory exists. This study aims to develop the first formal grounded theory in marketing by incorporating artificial intelligence and Forde's conceptual framework as a guiding lens. Charmaz's constructivist grounded theory tradition and Forde's conceptual framework and data analysis strategy were employed for this purpose. The (...) data analysis strategy used with grounded theory’s constant compare-and-contrast method comprises holistic and systems thinking, dramaturgical and situational analysis, perspective-taking, and deconstruction. To evaluate Glaser’s assertion that all is data, artificial intelligence was incorporated into the research as the data source for retrieving the theoretical samples to address the primary research question: How can Forde's conceptual framework and artificial intelligence be leveraged to develop a formal marketing theory grounded in evidence? Of significance was the emergence of democratic marketing behaviors and the normalization of anti-democratic marketing approaches leveraged to manipulate buyers or gain access to segments of customers. Buyers and sellers can simultaneously benefit from and be prejudiced by marketing exchange dynamics. This finding lends credibility to the newly emerged framework of strategic actions where empowerment and disempowerment are leveraged to achieve specific goals. Considering this finding, it is suggested that businesses view marketing as a symbiotic relationship between two power centers, buyers and sellers, who respectively strive to maintain human dignity and sustainability. Researchers are encouraged to apply the framework across substantive areas, international markets, public relations, political campaigns, and others. (shrink)

Students often have difficulty connecting theoretical and text-based scholarship to the real world. When teaching in Asia, this disconnection is exacerbated by the European/American focus of many canonical texts, whereas students' own experiences are primarily Asian. However, in my discipline of political philosophy, this problem receives little recognition nor is it comprehensively addressed. In this paper, I propose that the problem must be taken seriously, and I share my own experiences with a novel pedagogical strategy which might offer a possible (...) path forward. Recent scholarship has championed an active learning approach, where students engage in their own research, and deliver outward-facing products that have a meaning and purpose beyond the confines of the student-professor relationship. In this spirit, I have put into practice a strategy of course design, where active learning is used to overcome students' disconnection with the course content. In particular, as a major component of course assessment, students are required to write an 'opinion piece', which is then showcased on a public website. The opinion piece must address a real-world issue which the student himself or herself selects and deems important; furthermore, it must build on the theoretical tools of the course and be written in a style which makes it accessible to a wider audience. I discuss the implementation of this strategy in two political philosophy courses, including strategies to avoid 'dumbing down' and ‘diluting’ the process of critical thinking. While no formal analysis of impact of the strategy on learning outcomes has been conducted, an anonymous pedagogical survey has yielded an overwhelmingly positive response for students' self-reported perceptions of the curricular innovations. (shrink)

Philosophy and Phenomenological Research, EarlyView.

Necessity and sufficiency are the building blocks of all successful explanations. Yet despite their importance, these notions have been conceptually underdeveloped and inconsistently applied in explainable artificial intelligence (XAI), a fast-growing research area that is so far lacking in firm theoretical foundations. Building on work in logic, probability, and causality, we establish the central role of necessity and sufficiency in XAI, unifying seemingly disparate methods in a single formal framework. We provide a sound and complete algorithm for computing explanatory (...) factors with respect to a given context, and demonstrate its flexibility and competitive performance against state of the art alternatives on various tasks. (shrink)

A theory of learning for the future advocates the teaching of a preparedness to respond in a creative way to difference and otherness. This includes an ability to act imaginatively in situations of uncertainties. John Dewey’s pragmatism holds the key to such a learning theory his view of the continuous meetings of individuals and environments as experimental and playful. That pragmatism has not yet been acknowledged as a relevant learning theory for the future may (...) be due to the immediate connotation and the many interpretations associated with the term ‘experience’, which is at the heart of Dewey’s educational thinking. Dewey defi ned experience in a way that is not well understood within educational research, and in a way that is easily confused with the term ‘experiential learning’. The latter refers to the importance of participants’ ‘experiences’ derived from bodily actions and stored in memory as more or less tacit knowledge. (shrink)

Dialectic, as commonly approached, is not an analytic study, as the notion is defined in the paper. Where it is analytically approached (as, for example, by Grice and Hamblin), the result is pragmatic in nature, as well as syntactic and semantic. This paper lays the foundations of a purely formal (nonpragmatic) analysis of conversations. This study is accordingly called "Conversation Theory". The key notions of "conversation", "dialogue", "conversation game", "rules of response", "epistemic community" and "channel of informations" are (...) defined precisely, and an analysis of how these notions fit together is given. Particular attention is given to distinguishing conversation theory from standard logic. The paper concludes by analysing a few sample conversation-games, indicating areas needing further research, by pointing out the simplification inherent in the sample games. (shrink)

Recent debate about the error theory has taken a ‘formal turn’. On the one hand, there are those who argue that the error theory should be rejected because of its difficulties in providing a convincing formal account of the logic and semantics of moral claims. On the other hand, there are those who claim that such formal objections fail, maintaining that arguments against the error theory must be of a substantive rather than a (...) class='Hi'>formal kind. In this paper, we argue that formal objections to the error theory cannot be eschewed but must be met head-on. (shrink)

Inspired by impossibility theorems of social choice theory, many democratic theorists have argued that aggregative forms of democracy cannot lend full democratic justification for the collective decisions reached. Hence, democratic theorists have turned their attention to deliberative democracy, according to which “outcomes are democratically legitimate if and only if they could be the object of a free and reasoned agreement among equals” (Cohen 1997a, 73). However, relatively little work has been done to offer a formal theory of (...) democratic deliberation. This article helps fill that gap by offering a formal theory of three different modes of democratic deliberation: myopic discussion, constructive discussion, and debate. We show that myopic discussion suffers from indeterminacy of long run outcomes, while constructive discussion and debate are conclusive. Finally, unlike the other two modes of deliberation, debate is path independent and converges to a unique compromise position, irrespective of the initial status quo. (shrink)

One of the tasks of ontology in information science is to support the classification of entities according to their kinds and qualities. We hold that to realize this task as far as entities such as material objects are concerned we need to distinguish four kinds of entities: substance particulars, quality particulars, substance universals, and quality universals. These form, so to speak, an ontological square. We present a formal theory of classification based on this idea, including both a semantics (...) for the theory and a provably sound axiomatization. (shrink)

Formal ontology as it is presented in Husserl`s Third Logical Investigation can be interpreted as a fundamental tool to describe objects in a formal sense. It is presented one of the main sources: chapter five of Carl Stumpf`s Ûber den psycholoogischen Ursprung der Raumovorstellung (1873), and then it is described how Husserlian Formal Ontology is applied in Fifth Logical Investigation. Finally, it is applied to dramatic structures, in the spirit of Roman Ingarden.

In everyday life it is often important to have a mental model of the knowledge, beliefs, desires, and intentions of other people. Sometimes it is even useful to to have a correct model of their model of our own mental states: a second-order Theory of Mind. In order to investigate to what extent adults use and acquire complex skills and strategies in the domains of Theory of Mind and the related skill of natural language use, we conducted an (...) experiment. It was based on a strategic game of imperfect information, in which it was beneficial for participants to have a good mental model of their opponent, and more specifically, to use second-order Theory of Mind. It was also beneficial for them to be aware of pragmatic inferences and of the possibility to choose between logical and pragmatic language use. We found that most participants did not seem to acquire these complex skills during the experiment when being exposed to the game for a number of different trials. Nevertheless, some participants did make use of advanced cognitive skills such as second-order Theory of Mind and appropriate choices between logical and pragmatic language use from the beginning. Thus, the results differ markedly from previous research. (shrink)

By separating the general concept of truth into syntactic truth and semantic truth, this article proposes a new theory of truth to explain several paradoxes like the Liar paradox, Card paradox, Curry’s paradox, etc. By revealing the relationship between syntactic /semantic truth and being-nothing-becoming which are the core concepts of dialectical logic, it is able to formalize dialectical logic. It also provides a logical basis for complexity theory by transferring all reasoning into a directed (cyclic/acyclic) graph which explains (...) both paradoxical and paradox-free reasoning. The different structure between cyclic graphs and acyclic graphs is the key to understanding paradoxes. By explaining the immanent between logic, paradox, and cellular automata, it also illustrates dialectical logic as ontology. (shrink)

Husserl’s theory of manifolds was developed for the first time in a very short form in the Prolegomena to his Logical Investigations, §§ 69–70 (pp. 248–53), then repeatedly discussed in Ideas I, §§ 71–2 (pp. 148–53), in Formal and Transcendental Logic, §§ 51–4 (pp. 142–54), and finally in the Crisis, § 9 (pp. 20–60). Husserl never lost sight of it: it was his idée fixe. He discussed this theme over forty years, expressing the same, in principle, ideas on (...) it in different terms and versions. His discussions of it, however, were always cut short and inconclusive, so that he never developed his theory of manifolds in detail. Main claim in this essay is that Husserl’s theory of manifolds is twofold. It is (1) a theory of theories, advanced in the good German tradition of Wissenschaftslehre, launched first by Bernard Bolzano. The latter, in turn, is an offspring of the ancient tradition of mathesis universalis, explored in the modernity by Descartes and Leibniz. Further, (2) the theory of manifolds is also a formal theory of everything. Its objective is to provide a systematic account of how the things in the world (its parts) hang together in wholes of quite different kind. It is to be noted that Husserl explicitly speaks about (1) and only implicitly about (2). In this paper we shall also show that the theory of everything is intrinsically connected with the theory of theories. (shrink)

A compact overview of the main formal theories of parthood and of their mutual relationships, up to Classical Extensional Mereology. Written as an Appendix to the other essays included in the volume.

Theory of Computation -- Computation by Abstracts Devices.

This is our journal for developing Deduction Theory and studying Deep Learning and Artificial intelligence. Deduction Theory is a Theory of Deducing World’s Relativity by Information Coupling and Asymmetry. We focus on information processing, see intelligence as an information structure that relatively close object-oriented, probability-oriented, unsupervised learning, relativity information processing and massive automated information processing. We see deep learning and machine learning as an attempt to make all types of information processing relatively close (...) to probability information processing. We will discuss about how to understand Deep Learning and Artificial intelligence and why Deep Learning is shown better performance than the other methods by metaphysical logic. (shrink)

Weisberg ([2009]) provides an argument that neither conditionalization nor Jeffrey conditionalization is capable of accommodating the holist’s claim that beliefs acquired directly from experience can suffer undercutting defeat. I diagnose this failure as stemming from the fact that neither conditionalization nor Jeffrey conditionalization give any advice about how to rationally respond to theory-dependent evidence, and I propose a novel updating procedure that does tell us how to respond to evidence like this. This holistic updating rule yields conditionalization as a (...) special case in which our evidence is entirely theory independent. 1 Introduction2 Conditionalization3 Holism and Conditionalization4 A Holistic Update5 HCondi and Dutch Books6 Commutativity and Learning about Background Theories6.1 Commutativity6.2 Learning about background theories7 In Summation. (shrink)

Since the beginning of the 20th Century to the present day, it has rarely been doubted that whenever formal aesthetic methods meet their iconological counterparts, the two approaches appear to be mutually exclusive. In reality, though, an ahistorical concept is challenging a historical analysis of art. It is especially Susanne K. Langer´s long-overlooked system of analogies between perceptions of the world and of artistic creations that are dependent on feelings which today allows a rapprochement of these positions. Krois’s insistence (...) on a similar point supports this analysis. - I - Unbestritten bis heute gilt, formwissenschaftliche und ikonologische Methoden scheinen sich grundsätzlich auszuschließen, da die ersteren auf ahistorischen und die letzteren auf historischen Grundlagen aufbauen. Dem entgegen soll mit diesem Beitrag gezeigt werden, wie insbesondere die Forschungen Susanne K. Langers und ergänzend diejenigen von John M. Krois eine Annäherung beider Positionen ermöglichen. (shrink)

Mencius, referred to as second sage in Chinese philosophy history, grounds his theory about original goodness of human nature on psychological components by bringing in something new down ancient ages. Including the principles of virtuous action associated with Confucius to his doctrine, but by composing them along psychosocial development, he theorizes utterly out of the ordinary that makes all the difference to the school. In his argument stated a positive opinion, he explains the method of forming individuals' moral awareness (...) by means of inseparable integrity of feelings and thoughts, saying human being are born innately good. According to Mencius, heart-mind correlation is the motivational complement of inner incentives. Knowledge and virtue, which are extensions of inborn goodness, comprehended intuitively; then affective motives respond to circumstance, what is learned transmits to cognitive process and eventually behavior emerges. Comparing during the years of Warring State period he lived, in western geography Aristotle, who is one of the pioneers of Greek philosophy, argues deductive and inductive methods in mental activity. On the other hand, Mencius uses analogical reasoning throughout his self-titled work. This essay is an attempt to assert that most postulates of developmental theories, which have been considered an integral part of modern psychology, begin with Mencius in early era. Secondly, this study also aims to discuss the main paradigm of Mencius across emotivist-rationalist opposition, which keeps emotion above thought as well as reason above emotion. (shrink)

This article provides the foundation for a new predictive theory of animal learning that is based upon a simple logical model. The knowledge of experimental subjects at a given time is described using logical equations. These logical equations are then used to predict a subject’s response when presented with a known or a previously unknown situation. This new theory suc- cessfully anticipates phenomena that existing theories predict, as well as phenomena that they cannot. It provides a theoretical (...) account for phenomena that are beyond the domain of existing models, such as extinction and the detection of novelty, from which “external inhibition” can be explained. Examples of the methods applied to make predictions are given using previously published results. The present theory proposes a new way to envision the minimal functions of the nervous system, and provides possible new insights into the way that brains ultimately create and use knowledge about the world. (shrink)

The definition of thinking in general form is given. The constructive logic of thinking is formulated. An algorithm capable of arbitrarily complex thinking is built.

This paper explores the individualism-holism debate in social ontology and proposes a novel approach to the formalization of our intuitions and claims about social entities. Responding to recent calls for gradualist approaches in lieu of traditional sum-zero scenarios, it is argued that formal tools can be extracted from Integrated Information Theory (IIT) that provide a suitable logical language for gradualist descriptions and analyses of social entities.

A discussion of John Dewey's theory of inquiry and what it does and does not imply concerning good educational practice.

Since the time of Aristotle's students, interpreters have considered Prior Analytics to be a treatise about deductive reasoning, more generally, about methods of determining the validity and invalidity of premise-conclusion arguments. People studied Prior Analytics in order to learn more about deductive reasoning and to improve their own reasoning skills. These interpreters understood Aristotle to be focusing on two epistemic processes: first, the process of establishing knowledge that a conclusion follows necessarily from a set of premises (that is, on the (...) epistemic process of extracting information implicit in explicitly given information) and, second, the process of establishing knowledge that a conclusion does not follow. Despite the overwhelming tendency to interpret the syllogistic as formal epistemology, it was not until the early 1970s that it occurred to anyone to think that Aristotle may have developed a theory of deductive reasoning with a well worked-out system of deductions comparable in rigor and precision with systems such as propositional logic or equational logic familiar from mathematical logic. When modern logicians in the 1920s and 1930s first turned their attention to the problem of understanding Aristotle's contribution to logic in modern terms, they were guided both by the Frege-Russell conception of logic as formal ontology and at the same time by a desire to protect Aristotle from possible charges of psychologism. They thought they saw Aristotle applying the informal axiomatic method to formal ontology, not as making the first steps into formal epistemology. They did not notice Aristotle's description of deductive reasoning. Ironically, the formal axiomatic method (in which one explicitly presents not merely the substantive axioms but also the deductive processes used to derive theorems from the axioms) is incipient in Aristotle's presentation. Partly in opposition to the axiomatic, ontically-oriented approach to Aristotle's logic and partly as a result of attempting to increase the degree of fit between interpretation and text, logicians in the 1970s working independently came to remarkably similar conclusions to the effect that Aristotle indeed had produced the first system of formal deductions. They concluded that Aristotle had analyzed the process of deduction and that his achievement included a semantically complete system of natural deductions including both direct and indirect deductions. Where the interpretations of the 1920s and 1930s attribute to Aristotle a system of propositions organized deductively, the interpretations of the 1970s attribute to Aristotle a system of deductions, or extended deductive discourses, organized epistemically. The logicians of the 1920s and 1930s take Aristotle to be deducing laws of logic from axiomatic origins; the logicians of the 1970s take Aristotle to be describing the process of deduction and in particular to be describing deductions themselves, both those deductions that are proofs based on axiomatic premises and those deductions that, though deductively cogent, do not establish the truth of the conclusion but only that the conclusion is implied by the premise-set. Thus, two very different and opposed interpretations had emerged, interestingly both products of modern logicians equipped with the theoretical apparatus of mathematical logic. The issue at stake between these two interpretations is the historical question of Aristotle's place in the history of logic and of his orientation in philosophy of logic. This paper affirms Aristotle's place as the founder of logic taken as formal epistemology, including the study of deductive reasoning. A by-product of this study of Aristotle's accomplishments in logic is a clarification of a distinction implicit in discourses among logicians--that between logic as formal ontology and logic as formal epistemology. (shrink)

The theories of belief change developed within the AGM-tradition are not logics in the proper sense, but rather informal axiomatic theories of belief change. Instead of characterizing the models of belief and belief change in a formalized object language, the AGM-approach uses a natural language — ordinary mathematical English — to characterize the mathematical structures that are under study. Recently, however, various authors such as Johan van Benthem and Maarten de Rijke have suggested representing doxastic change within a formal (...) logical language: a dynamic modal logic. Inspired by these suggestions Krister Segerberg has developed a very general logical framework for reasoning about doxastic change: dynamic doxastic logic (DDL). This framework may be seen as an extension of standard Hintikka-style doxastic logic with dynamic operators representing various kinds of transformations of the agent's doxastic state. Basic DDL describes an agent that has opinions about the external world and an ability to change these opinions in the light of new information. Such an agent is non-introspective in the sense that he lacks opinions about his own belief states. Here we are going to discuss various possibilities for developing a dynamic doxastic logic for introspective agents: full DDL or DDL unlimited. The project of constructing such a logic is faced with difficulties due to the fact that the agent’s own doxastic state now becomes a part of the reality that he is trying to explore: when an introspective agent learns more about the world, then the reality he holds beliefs about undergoes a change. But then his introspective (higher-order) beliefs have to be adjusted accordingly. In the paper we shall consider various ways of solving this problem. (shrink)

Modularity theorists have challenged that there are, or could be, general learning mechanisms that explain theory-of-mind development. In response, supporters of the ‘scientific theory-theory’ account of theory-of-mind development have appealed to children's use of auxiliary hypotheses and probabilistic causal modeling. This article argues that these general learning mechanisms are not sufficient to meet the modularist's challenge. The article then explores an alternative domain-general learning mechanism by proposing that children grasp the concept belief through (...) the progressive alignment of relational structure that occurs as a result of structural-comparison. The article also explores the implications of the proposed account for Fodor's puzzle of conceptual learning. (shrink)

An important problem with machine learning is that when label number n>2, it is very difficult to construct and optimize a group of learning functions, and we wish that optimized learning functions are still useful when prior distribution P(x) (where x is an instance) is changed. To resolve this problem, the semantic information G theory, Logical Bayesian Inference (LBI), and a group of Channel Matching (CM) algorithms together form a systematic solution. MultilabelMultilabel A semantic channel in (...) the G theory consists of a group of truth functions or membership functions. In comparison with likelihood functions, Bayesian posteriors, and Logistic functions used by popular methods, membership functions can be more conveniently used as learning functions without the above problem. In Logical Bayesian Inference (LBI), every label’s learning is independent. For Multilabel learning, we can directly obtain a group of optimized membership functions from a big enough sample with labels, without preparing different samples for different labels. A group of Channel Matching (CM) algorithms are developed for machine learning. For the Maximum Mutual Information (MMI) classification of three classes with Gaussian distributions on a two-dimensional feature space, 2-3 iterations can make mutual information between three classes and three labels surpass 99% of the MMI for most initial partitions. For mixture models, the Expectation-Maxmization (EM) algorithm is improved and becomes the CM-EM algorithm, which can outperform the EM algorithm when mixture ratios are imbalanced, or local convergence exists. The CM iteration algorithm needs to combine neural networks for MMI classifications on high-dimensional feature spaces. LBI needs further studies for the unification of statistics and logic. (shrink)

This article presents a case study of the structure and logic of the author’s dissertation, with a focus on theoretical content. Designed for use in proposal writing seminars or research methods courses, the article stresses the value of identifying the originating, specifying and subsidiary research questions; clarifying the subject and object of the research; situating research within a particular research tradition, and using a competing theories approach. The article stresses the need to identify conceptual problems and empirical problems and their (...) associated conceptual and operational definitions. The primary theoretical perspective is drawn from emerging sociology of externalities rooted in ecological theory, within the institutionalist tradition. (shrink)

The first decade of this century has seen the nascency of the first mathematical theory of general artificial intelligence. This theory of Universal Artificial Intelligence (UAI) has made significant contributions to many theoretical, philosophical, and practical AI questions. In a series of papers culminating in book (Hutter, 2005), an exciting sound and complete mathematical model for a super intelligent agent (AIXI) has been developed and rigorously analyzed. While nowadays most AI researchers avoid discussing intelligence, the award-winning PhD thesis (...) (Legg, 2008) provided the philosophical embedding and investigated the UAI-based universal measure of rational intelligence, which is formal, objective and non-anthropocentric. Recently, effective approximations of AIXI have been derived and experimentally investigated in JAIR paper (Veness et al. 2011). This practical breakthrough has resulted in some impressive applications, finally muting earlier critique that UAI is only a theory. For the first time, without providing any domain knowledge, the same agent is able to self-adapt to a diverse range of interactive environments. For instance, AIXI is able to learn from scratch to play TicTacToe, Pacman, Kuhn Poker, and other games by trial and error, without even providing the rules of the games. These achievements give new hope that the grand goal of Artificial General Intelligence is not elusive. This article provides an informal overview of UAI in context. It attempts to gently introduce a very theoretical, formal, and mathematical subject, and discusses philosophical and technical ingredients, traits of intelligence, some social questions, and the past and future of UAI. (shrink)

This paper attempts to answer a central question in unsupervised learning: what does it mean to “make sense” of a sensory sequence? In our formalization, making sense involves constructing a symbolic causal theory that both explains the sensory sequence and also satisfies a set of unity conditions. The unity conditions insist that the constituents of the causal theory – objects, properties, and laws – must be integrated into a coherent whole. On our account, making sense of sensory (...) input is a type of program synthesis, but it is unsupervised program synthesis. Our second contribution is a computer implementation, the Apperception Engine, that was designed to satisfy the above requirements. Our system is able to produce interpretable human-readable causal theories from very small amounts of data, because of the strong inductive bias provided by the unity conditions. A causal theory produced by our system is able to predict future sensor readings, as well as retrodict earlier readings, and impute (fill in the blanks of) missing sensory readings, in any combination. In fact, it is able to do all three tasks simultaneously. We tested the engine in a diverse variety of domains, including cellular automata, rhythms and simple nursery tunes, multi-modal binding problems, occlusion tasks, and sequence induction intelligence tests. In each domain, we test our engine's ability to predict future sensor values, retrodict earlier sensor values, and impute missing sensory data. The Apperception Engine performs well in all these domains, significantly out-performing neural net baselines. We note in particular that in the sequence induction intelligence tests, our system achieved human-level performance. This is notable because our system is not a bespoke system designed specifically to solve intelligence tests, but a general-purpose system that was designed to make sense of any sensory sequence. (shrink)

I propose that metaphysical study is initially indifferent to the truth of Metaphysical Realism about Metaphysics (MRM) and Metaphysical Realism and does not presuppose them. Metaphysical Realism is a metaphysical doctrine the truth of which cannot be settled logically prior to metaphysical investigation. MRM presupposes Metaphysical Realism and therefore, one should not hold MRM uncritically. An epistemological consequence of this is that arguments against the possibility of cognition about metaphysically real entities (by e.g., Hume) are not arguments against the epistemic (...) legitimacy of metaphysics without further arguments for MRM. This paper is also a case study of the philosophical significance of having rich enough acquaintance with the history of philosophy, the recent history included. (shrink)

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx.

Orthodox Bayesianism is a highly idealized theory of how we ought to live our epistemic lives. One of the most widely discussed idealizations is that of logical omniscience: the assumption that an agent’s degrees of belief must be probabilistically coherent to be rational. It is widely agreed that this assumption is problematic if we want to reason about bounded rationality, logical learning, or other aspects of non-ideal epistemic agency. Yet, we still lack a satisfying way to avoid logical (...) omniscience within a Bayesian framework. Some proposals merely replace logical omniscience with a different logical idealization; others sacrifice all traits of logical competence on the altar of logical non-omniscience. We think a better strategy is available: by enriching the Bayesian framework with tools that allow us to capture what agents can and cannot infer given their limited cognitive resources, we can avoid logical omniscience while retaining the idea that rational degrees of belief are in an important way constrained by the laws of probability. In this paper, we offer a formal implementation of this strategy, show how the resulting framework solves the problem of logical omniscience, and compare it to orthodox Bayesianism as we know it. (shrink)

How does one formalize the structure of structures necessary for the foundations of physics? This work is an attempt at conceptualizing the metaphysics of pregeometric structures, upon which new and existing notions of quantum geometry may find a foundation. We discuss the philosophy of pregeometric structures due to Wheeler, Leibniz as well as modern manifestations in topos theory. We draw attention to evidence suggesting that the framework of formal language, in particular, homotopy type theory, provides the conceptual (...) building blocks for a theory of pregeometry. This work is largely a synthesis of ideas that serve as a precursor for conceptualizing the notion of space in physical theories. In particular, the approach we espouse is based on a constructivist philosophy, wherein ``structureless structures'' are syntactic types realizing formal proofs and programs. Spaces and algebras relevant to physical theories are modeled as type-theoretic routines constructed from compositional rules of a formal language. This offers the remarkable possibility of taxonomizing distinct notions of geometry using a common theoretical framework. In particular, this perspective addresses the crucial issue of how spatiality may be realized in models that link formal computation to physics, such as the Wolfram model. (shrink)

I argue that normative formal epistemology (NFE) is best understood as modelling, in the sense that this is the reconstruction of its methodology on which NFE is doing best. I focus on Bayesianism and show that it has the characteristics of modelling. But modelling is a scientific enterprise, while NFE is normative. I thus develop an account of normative models on which they are idealised representations put to normative purposes. Normative assumptions, such as the transitivity of comparative credence, are (...) characterised as modelling idealisations motivated normatively. I then survey the landscape of methodological options: what might formal epistemologists be up to? I argue the choice is essentially binary: modelling or theorising. If NFE is theorising it is doing very poorly: generating false claims with no clear methodology for separating out what is to be taken seriously. Modelling, by contrast, is a successful methodology precisely suited to the management of useful falsehoods. Regarding NFE as modelling is not costless, however. First, our normative inferences are less direct and are muddied by the presence of descriptive idealisations. Second, our models are purpose-specific and limited in their scope. I close with suggestions for how to adapt our practice. (shrink)

Artificial Psychology (AP) is a highly multidisciplinary field of study in psychology. AP tries to solve problems which occur when psychologists do research and need a robust analysis method. Conventional statistical approaches have deep rooted limitations. These approaches are excellent on paper but often fail to model the real world. Mind researchers have been trying to overcome this by simplifying the models being studied. This stance has not received much practical attention recently. Promoting and improving artificial intelligence helps mind researchers (...) to find a holistic model of mental models. This development achieves this goal by using multiple perspectives and multiple data sets together with interactive, and realistic models. In this book, the methodology of approximate inference in psychological research from a theoretical and practical perspective has been considered. Quantitative variable-oriented methodology and qualitative case-oriented methods are both used to explain the set-oriented methodology and this book combines the precision of quantitative methods with information from qualitative methods. This is a book that many researchers can use to expand and deepen their psychological research and is a book which can be useful to postgraduate students. The reader does not need an in-depth knowledge of mathematics or statistics because statistical and mathematical intuitions are key here and they will be learned through practice. What is important is to understand and use the new application of the methods for finding new, dynamic and realistic interpretations. This book incorporates theoretical fuzzy inference and deep machine learning algorithms in practice. This is the kind of book that we wished we had had when we were students. This book covers at least some of the most important issues in mind research including uncertainty, fuzziness, continuity, complexity and high dimensionality which are inherent to mind data. These are elements of artificial psychology. This book implements models using R software. (shrink)

Issues of reliability are claiming center-stage in the epistemology of machine learning. This paper unifies different branches in the literature and points to promising research directions, whilst also providing an accessible introduction to key concepts in statistics and machine learning---as far as they are concerned with reliability.

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)

Extended and distributed cognition theories argue that human cognitive systems sometimes include non-biological objects. On these views, the physical supervenience base of cognitive systems is thus not the biological brain or even the embodied organism, but an organism-plus-artifacts. In this paper, we provide a novel account of the implications of these views for learning, education, and assessment. We start by conceptualising how we learn to assemble extended cognitive systems by internalising cultural norms and practices. Having a better grip on (...) how extended cognitive systems are assembled, we focus on the question: If our cognition extends, how should we educate and assess such extended cognitive systems? We suggest various ways to minimize possible negative effects of extending one’s cognition and to efficiently find and organise (online) information by adopting a virtue epistemology approach. Educational and assessment implications are foregrounded, particularly in the case of Danish students’ use of the Internet during exams. (shrink)

Over the last two decades, the capabilities approach has become an increasingly influential theory of development. It conceptualises human wellbeing in terms of an individual's ability to achieve functionings we have reason to value. In contrast, the African ethic of ubuntu views human flourishing as the propensity to pursue relations of fellowship with others, such that relationships have fundamental value. These two theoretical perspectives seem to be in tension with each other; while the capabilities approach focuses on individuals as (...) the locus of ethical value, an ubuntu ethic concentrates on the relations between individuals. In this article, we ask: to what extent is the capabilities approach compatible with this African ethical theory? We argue that, on reflection, relations play a much stronger role in the capabilities approach than often assumed. There is good reason to believe that relationality is part of the concept of a capability itself, where such relationality has intrinsic ethical value. This understanding of the ethical centrality of relations grounds new normative perspectives on the capabilities approach, and offers a more comprehensive grasp of the relevance of relationships to empirical enquiry. (shrink)

It is commonly said that some standards, such as morality, are ‘normatively authoritative’ in a way that other standards, such as etiquette, are not; standards like etiquette are said to be ‘not really normative’. Skeptics deny the very possibility of normative authority, and take claims like ‘etiquette is not really normative’ to be either empty or confused. I offer a different route to defeat skeptics about authority: instead of focusing on what makes standards like morality special, we should focus on (...) what makes standards like etiquette ‘not really normative’. I defend a fictionalist theory on which etiquette is ‘not really normative’ in roughly the same way that Sherlock is ‘not really a detective’, and show that fictionalism about some normative standards helps us explain the possibility of normative authority. (shrink)