Vādanyāya is one of the representative works of Dharmakīrti. It is concerned with debate logic and deals with win-or-lose reasoning rules in the broad sense of logic. In this paper, we will concentrate our discussion on Dharmakīrti’s theory of nigrahasthāna (fault) in his debate logic, a key issue in Vādanyāya. First, we point out that the justification of three logical reasons as proof conditions of debate constitutes the rational point of departure for Dharmakīrti’s debate logic. Second, we analyze the differences (...) between Dharmakīrti’s and the Naiyāyika’s notion of debate and point out that Dharmakīrti’s ‘debate’ involves two parties (the disputant and the opponent) attempting to rationally refute the other’s opinion to persuade the other to change their wrong ideas. Last, based on the discussion of Dharmakīrti’s concept of debate logic, we identify seven types of nigrahasthāna in Vādanyāya with regard to the two parties of a debate (the disputant and the opponent). (shrink)

Beyond modularityattempts a synthesis of Fodor's anticonstructivist nativism and Piaget's antinativist constructivism. Contra Fodor, I argue that: (1) the study of cognitive development is essential to cognitive science, (2) the module/central processing dichotomy is too rigid, and (3) the mind does not begin with prespecified modules; rather, development involves a gradual process of “modularization.” Contra Piaget, I argue that: (1) development rarely involves stagelike domain-general change and (2) domainspecific predispositions give development a small but significant kickstart by (...) focusing the infant's attention on proprietary inputs. Development does not stop at efficient learning. A fundamental aspect of human development (“representational redescription”) is the hypothesized process by which information that isina cognitive system becomes progressively explicit knowledgetothat system. Development thus involves two complementary processes of progressive modularization and progressive “explicitation.” Empirical findings on the child as linguist, physicist, mathematician, psychologist, and notator are discussed in support of the theoretical framework. Each chapter concentrates first on the initial state of the infant mind/brain and on subsequent domain-specific learning in infancy and early childhood. It then goes on to explore data on older children's problem solving and theory building, with particular focus on evolving cognitive flexibility. Emphasis is placed throughout on the status of representations underlying different capacities and on the multiple levels at which knowledge is stored and accessible. Finally, consideration is given to the need for more formal developmental models, and a comparison is made between representational redescription and connectionist simulations of development. In conclusion, I consider what is special about human cognition by speculating on the status of representations underlying the structure of behavior in other species. (shrink)

Common sense is on the one hand a certain set of processes of natural cognition - of speaking, reasoning, seeing, and so on. On the other hand common sense is a system of beliefs (of folk physics, folk psychology and so on). Over against both of these is the world of common sense, the world of objects to which the processes of natural cognition and the corresponding belief-contents standardly relate. What are the structures of this world? How does the scientific (...) treatment of this world relate to traditional and contemporary metaphysics and formal ontology? Can we embrace a thesis of common-sense realism to the effect that the world of common sense exists uniquely? Or must we adopt instead a position of cultural relativism which would assign distinct worlds of common sense to each group and epoch? The present paper draws on recent work in computer science (especially in the fields of naive and qualitative physics), in perceptual and developmental psychology, and in cognitive anthropology, in order to consider in a new light these and related questions and to draw conclusions for the methodology and philosophical foundations of the cognitive sciences. (shrink)

Talk of levels is everywhere in cognitive science. Whether it is in terms of adjudicating longstanding debates or motivating foundational concepts, one cannot go far without hearing about the need to talk at different ‘levels’. Yet in spite of its widespread application and use, the concept of levels has received little sustained attention within cognitive science. This paper provides an analysis of the various ways the notion of levels has been deployed within cognitive science. (...) The paper begins by introducing and motivating discussion via four representative accounts of levels. It then turns to outlining and relating the four accounts using two dimensions of comparison. The result is the creation of a conceptual framework that maps the logical space of levels talk, which offers an important step toward making sense of levels talk within cognitive science. (shrink)

We support the development of non-reductive cognitive science and the naturalization of phenomenology for this purpose, and we agree that the ‘relational turn’ defended by Gallagher is a necessary step in this direction. However, we believe that certain aspects of his relational concept of nature need clarification. In particular, Gallagher does not say whether or how teleology, affect, and other value-related properties of life and mind can be naturalized within this framework. In this paper, we argue that (1) (...) given the phenomenological standards recognized by Gallagher, his commitment to a naturalized phenomenology should entail a commitment to a naturalized concept of value; and (2) the kind of ‘relational nature’ described by Gallagher in his paper is insufficient for this purpose. (shrink)

8.6 Issues Raised by the Algorithms Proposed.

A number of recent publications have argued that a scientific approach to consciousness needs a rigorous approach to first-person data collection. As mainstream experimental psychology has long abandoned such introspective or phenomenological method, there is at present no generally agreed upon method for first-person data collection in experimental consciousness studies. There are, however, a number of recent articles that all claim to provide a unique contribution to such a methodology. This article reviews these suggestions and extracts their core features. It (...) is argued that the suggested methods are generally overlapping and compatible, and a number of concrete methods that easily are applied to experimental studies are put forward. (shrink)

The Phenomenological Mind, by Shaun Gallagher and Dan Zahavi, is part of a recent initiative to show that phenomenology, classically conceived as the tradition inaugurated by Edmund Husserl and not as mere introspection, contributes something important to cognitive science. (For other examples, see “References” below.) Phenomenology, of course, has been a part of cognitive science for a long time. It implicitly informs the works of Andy Clark (e.g. 1997) and John Haugeland (e.g. 1998), and Hubert Dreyfus (...) explicitly uses it (e.g. 1992). But where the former use phenomenology in the background as broad context and Dreyfus uses it primarily (though not exclusively) as a critique of conventional AI, Gallagher and Zahavi wish to indicate a positive and constructive place for it within cognitive science. They do not recommend that we simply accept pronouncements of thinkers like Husserl, Heidegger, Sartre and Merleau‐Ponty and apply them to questions of cognition, but that we use revised forms of phenomenology to illuminate dimensions of cognitive experience that are missing in current research. The book is presented as an “introduction to philosophy of mind and cognitive science” written from a phenomenological perspective. It seeks to justify the use of phenomenology in cognitive science by showing what kinds of questions it asks and answers, the variety of uses to which it has recently been put and the fruitfulness of some of its findings. The catalog of topics, for the most part, matches other introductions to the philosophy of mind, such as questions of method, consciousness, perception, intentionality, embodiment, action, agency and other minds. One issue presented here that is not generally dealt with in existing philosophy of mind and cognitive science texts is temporality, a mainstay of the continental tradition. After an introductory chapter that places phenomenology in the context of other approaches, the book lays out the main tenets of phenomenological method. Here, one encounters expected components of phenomenology: the epoché (described below), phenomenological reduction, eidetic variation, and so on. This traditional fare is soon followed by some potential surprises, namely, attempts to “naturalize” phenomenology, a few attempts to formalize it, and the emergence of ‘neurophenomenology’. Each of these is a bit surprising because Husserl was a vocal critic of naturalism, seeing transcendental phenomenology as an alternative to the empirical study of consciousness. He was also skeptical about the possibilities of mathematizing phenomenology. Gallagher and Zahavi acknowledge these points, but since they are not repeating history or undertaking exegesis, strict adherence to canonical phenomenology is not required. Naturalizing phenomenology means recognizing that “the phenomena it studies are part of nature and are therefore also open to empirical investigation” (p.. (shrink)

This essay examines the relevance of dynamical ideas for cognitive science. On its own, the mere mathematical idea of a dynamical system is too weak to serve as a scientific theory of anything, and dynamical approaches within cognitive science are too rich and varied to be subsumed under a single “dynamical hypothesis.” Instead, after first attempting to dissect the different notions of “dynamics” and “cognition” at play, a more specific theoretical framework for cognitive science (...) broadly construed is sketched. This framework draws upon not only dynamical ideas, but also such contemporaneous perspectives as situatedness, embodiment, ecological psychology, enaction, neuroethology/neuroscience, artificial life, and biogenic approaches. The paper ends with some methodological suggestions for pursuing this theoretical framework. (shrink)

Cognitive Science, Literature, and the Arts is the first student-friendly introduction to the uses of cognitive science in the study of literature, written specifically for the non-scientist. Patrick Colm Hogan guides the reader through all of the major theories of cognitive science, focusing on those areas that are most important to fostering a new understanding of the production and reception of literature. This accessible volume provides a strong foundation of the basic principles of (...) class='Hi'>cognitive science, and allows us to begin to understand how the brain works and makes us feel as we read. (shrink)

Cognitive science, as an interdisciplinary research endeavour, seeks to explain mental activities such as reasoning, remembering, language use, and problem solving, and the explanations it advances commonly involve descriptions of the mechanisms responsible for these activities. Cognitive mechanisms are distinguished from the mechanisms invoked in other domains of biology by involving the processing of information. Many of the philosophical issues discussed in the context of cognitive science involve the nature of information processing. For philosophy of (...) science, a central question is what counts as a scientific explanation. But what is a mechanistic explanation and how does it work, how can philosophy of science use it as a solution for the problem of integration in cognitive science? By answering these questions and merging my answers with discussion of concepts of philosophy, normativity and generality, I will investigate the following claim. -/- I claim that philosophy by using strength concepts such as normativity, generality, and a mechanistic philosophy of explanations, can be a most important contributor to cognitive science. I also investigate how philosophy of science could be (can be) a bridge between psychology and neuroscience. We need a distinction between philosophy of cognitive science and philosophy in cognitive science; I am talking about the latter. -/- This claim is very important for the integration and the future of the interdisciplinary field known as cognitive science. -/- Philosophy as a true cognitive science -/- When the Cognitive Science Society was founded, in the late 1970s, philosophy, neuroscience, and anthropology were playing smaller roles. The three disciplines that formed the core group were artificial intelligence, psychology, and linguistics. The curious thing is that George Miller, a psychologist and an important founder of cognitive sciences in a hexagon diagram that he presented, put philosophy at the top of the diagram and neuroscience at the very bottom. There is enough agreement now that neuroscience is the most important contributor to cognitive science and there are fair connections between philosophy and neuroscience. In that diagram there was almost no connection between philosophy and neuroscience. -/- The developments and rise of cognitive science in the last half-century has been accompanied by considerable amount of philosophical activity. Perhaps no other area within analytic philosophy in the second half of that period has attracted more attention or produced more publications. (Bechtel and Graham, 1998. Rumelhart and Bly 1999. Bechtel, Mandik, Mundale 2001. Thagard, 2007. Bennett and Dennett et al, 2007. Bennett and Hacker, 2008. Andler, 2009. Frankish and Ramsey, 2012.) -/- Many philosophers of science offer conclusions that have a direct bearing on cognitive science and its practitioners can profit from closer engagement with the rest of cognitive science. For example, William Bechtel has discussed three projects, two in naturalistic philosophy of mind and one in naturalistic philosophy of science that have been pursued during the past 30 years, that he contends, can make theoretical and methodological contributions to cognitive science (Bechtel, 2009). Paul Thagard is another example of the mentioned emerging school of philosophers of science that define cognitive science as the interdisciplinary investigation of mind and intelligence (Thagard, 2006). Thagard by presenting some general but important philosophical questions such as, “What is the nature of the explanations and theories developed in cognitive science?”, and by providing answers to these central questions has showed how philosophy of science can help cognitive science by the advantage of its generality. Andrew Brook, however, believes that philosophical approaches have never had a settled place in cognitive science but he is listed in a group of the philosophers of science that they are contributing very closely the cognitive science (Brook, 2009). Daniel Dennett , as well as being a member the mentioned naturalistic philosophers of science, believes that there is much good work for philosophers to do in cognitive science if they adopt the constructive attitude that prevails in science. -/- What are mechanisms? Let us begin abstractly before considering an example. Mechanisms are collections of entities and activities organized together to do something (cf. Machamer, Darden, & Craver, 2000; Craver & Darden, 2001; Bechtel &Richardson, 1993; Glennan, 1996). These explanations are known as ‘mechanistic explanations’. By using and developing these mechanistic explanations of philosophy of science one can draw normative consequences for cognitive science. Paul Thagard (Thagard, 2006 and 2009), William Bechtel (Bechtel, 2008 and 2009), Andrew Brook (Brook, 2008) investigated and promoted using the ‘normativity’ in philosophy to show a better and crucial role for philosophy of science in an interdisciplinary known as cognitive science. Some philosophers have thought that, in order to pursue this normative function, philosophy must distance itself from empirical matters, but there are examples where the investigations of descriptive and normative issues go hand in hand. ( Thagard, 2009). -/- I will investigate how we can reduce a higher-level science such as psychology to neuroscience without the problems of reductionism but via mechanistic explanations. By problem I mean psychology does not lose its autonomy. -/- Conclusion -/- If cognitive science is all about understanding the human mind, or if cognitive science is the interdisciplinary investigation of mind and intelligence, since the whole life of philosophy was involving with the ways of knowing (epistemology) and conceptions of reality (metaphysics), also philosophy has considered the so-called mind-body problem ( identity theory, functionalism, and heuristic identity theory) , then philosophy could be the most deserved discipline to be a most contributor in cognitive science. I tried to discuss this by using the three advantages in philosophy, normativity, and generality and by introducing an emerging school of mechanistic (not mechanical) philosophers. One thing left, as cognitive science is a two-way street, philosophers need also to stop in a station of cognitive science and learn from the most important advances in brain and neuroscience. -/- . (shrink)

Cognitive Science is a single-source undergraduate text that broadly surveys the theories and empirical results of cognitive science within a consistent computational perspective. In addition to covering the individual contributions of psychology, philosophy, linguistics, and artificial intelligence to cognitive science, the book has been revised to introduce the connectionist approach as well as the classical symbolic approach and adds a new chapter on cognitively related advances in neuroscience. Cognitive science is a rapidly (...) evolving field that is characterized by considerable contention among different views and approaches. Cognitive Science presents these in a relatively neutral manner. It covers many new orientations theories and findings, embedding them in an integrated computational perspective and establishing a sense of continuity and contrast with more traditional work in cognitive science. The text assumes no prerequisite knowledge, introducing all topics in a uniform, accessible style. Many topics, such as natural language processing and vision, however, are developed in considerable depth, which allows the book to be used with more advanced undergraduates or even in beginning graduate settings. A Bradford Book. (shrink)