Written in the 1960s, TRUTH AND METHOD is Gadamer's magnum opus. Looking behind the self-consciousness of science, he discusses the tense relationship between truth and methodology. In examining the different experiences of truth, he aims to "present the hermeneutic phenomenon in its fullest extent.

The paper explores the distinction between two doctrines, both of which inform theory construction in much of modern cognitive psychology: the representational theory of mind and the computational theory of mind. According to the former, propositional attitudes are to be construed as relations that organisms bear to mental representations. According to the latter, mental processes have access only to formal (nonsemantic) properties of the mental representations over which they are defined.The following claims are defended: (1) That the traditional dispute between (...) “rational” and “naturalistic” psychology is plausibly viewed as an argument about the status of the computational theory of mind. Rational psychologists accept a formality condition on the specification of mental processes; naturalists do not. (2) That to accept the formality condition is to endorse a version of methodological solipsism. (3) That the acceptance of some such condition is warranted, at least for that part of psychology which concerns itself with theories of the mental causation of behavior. This is because: (4) such theories require nontransparent taxonomies of mental states; and (5) nontransparent taxonomies individuate mental states without reference to their semantic properties. Equivalently, (6) nontransparent taxonomies respect the way that the organism represents the object of its propositional attitudes toitself, and it is this representation which functions in the causation of behavior.The final section of the paper considers the prospect for a naturalistic psychology: one which defines its generalizations over relations between mental representations and their environmental causes, thus seeking to account for the semantic properties of propositional attitudes. Two related arguments are proposed, both leading to the conclusion that no such research strategy is likely to prove fruitful. (shrink)

The appropriate methodology for psychological research depends on whether one is studying mental algorithms or their implementation. Mental algorithms are abstract specifications of the steps taken by procedures that run in the mind. Implementational issues concern the speed and reliability of these procedures. The algorithmic level can be explored only by studying across-task variation. This contrasts with psychology's dominant methodology of looking for within-task generalities, which is appropriate only for studying implementational issues.The implementation-algorithm distinction is related to a number of (...) other “levels” considered in cognitive science. Its realization in Anderson's ACT theory of cognition is discussed. Research at the algorithmic level is more promising because it is hard to make further fundamental scientific progress at the implementational level with the methodologies available. Protocol data, which are appropriate only for algorithm-level theories, provide a richer source than data at the implementational level. Research at the algorithmic level will also yield more insight into fundamental properties of human knowledge because it is the level at which significant learning transitions are defined.The best way to study the algorithmic level is to look for differential learning outcomes in pedagogical experiments that manipulate instructional experience. This provides control and prediction in realistically complex learning situations. The intelligent tutoring paradigm provides a particularly fruitful way to implement such experiments.The implications of this analysis for the issue of modularity of mind, the status of language, research on human/computer interaction, and connectionist models are also examined. (shrink)

Unlike the first English translation in 1974, this edition contains the text corresponding to Brentano's original 1874 edition.

The significance of consciousness in modern science is discussed by leading authorities from a variety of disciplines. Presenting a wide-ranging survey of current thinking on this important topic, the contributors address such issues as the status of different aspects of consciousness; the criteria for using the concept of consciousness and identifying instances of it; the basis of consciousness in functional brain organization; the relationship between different levels of theoretical discourse; and the functions of consciousness.

A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...) and neural models. The explanations of behavior provided are like those traditional in the physical sciences, unlike the explanations provided by symbolic models. (shrink)

This paper explores the difference between Connectionist proposals for cognitive a r c h i t e c t u r e a n d t h e s o r t s o f m o d e l s t hat have traditionally been assum e d i n c o g n i t i v e s c i e n c e . W e c l a i m t h a t t h (...) e m a j o r d i s t i n c t i o n i s t h a t , w h i l e b o t h Connectionist and Classical architectures postulate representational mental states, the latter but not the former are committed to a symbol-level of representation, or to a ‘language of thought’: i.e., to representational states that have combinatorial syntactic and semantic structure. Several arguments for combinatorial structure in mental representations are then reviewed. These include arguments based on the ‘systematicity’ of mental representation: i.e., on the fact that cognitive capacities always exhibit certain symmetries, so that the ability to entertain a given thought implies the ability to entertain thoughts with semantically related contents. We claim that such arguments make a powerful case that mind/brain architecture is not Connectionist at the cognitive level. We then consider the possibility that Connectionism may provide an account of the neural (or ‘abstract neurological’) structures in which Classical cognitive architecture is implemented. We survey a n u m b e r o f t h e s t a n d a r d a r g u m e n t s t h a t h a v e b e e n o f f e r e d i n f a v o r o f Connectionism, and conclude that they are coherent only on this interpretation. (shrink)

What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

Hilary Putnam, who may have been the first philosopher to advance the notion that the computer is an apt model for the mind, takes a radically new view of his...

Bruner sets forth nothing less than a new agenda for the study of the mind. He examines the irrepressibly human acts of imagination that allow us to make experience meaningful; he calls this side of mental activity the “narrative mode,” and his book makes important advances in the effort to unravel its nature.

the concept of modularity of cognitive processes is introduced and a picture of mind is proposed according to which the peripheral input systems are modular whereas the central processes are not. The present paper examines this view from both a methodological and a substaintive perspective. Methodologically, a contrast between considerations of principle and of fact is made and implications for the nature of cognitive theory are discussed. Substantively, constraints on information flow are examined as they appear in various aspects of (...) psychological phenomenology, and central processes in particular. It is suggested that the notion of modularity as structural and fixed be replaced by one which is dynamic, context-dependent. This modification, it is argued, is productive for the characterization of the workings of the mind, and it defines new questions for investigation. (shrink)

Understanding Computers and Cognition presents an important and controversial new approach to understanding what computers do and how their functioning is related to human language, thought, and action. While it is a book about computers, Understanding Computers and Cognition goes beyond the specific issues of what computers can or can't do. It is a broad-ranging discussion exploring the background of understanding in which the discourse about computers and technology takes place. Understanding Computers and Cognition is written for a wide audience, (...) not just those professionals involved in computer design or artificial intelligence. It represents an important contribution to the ongoing discussion about what it means to be a machine, and what it means to be human. Book jacket. (shrink)

This systematic investigation of computation and mental phenomena by a noted psychologist and computer scientist argues that cognition is a form of computation, that the semantic contents of mental states are encoded in the same general way as computer representations are encoded. It is a rich and sustained investigation of the assumptions underlying the directions cognitive science research is taking. 1 The Explanatory Vocabulary of Cognition 2 The Explanatory Role of Representations 3 The Relevance of Computation 4 The Psychological Reality (...) of Programs: Strong Equivalence 5 Constraining Functional Architecture 6 The Bridge from Physical to Symbolic: Transduction 7 Functional Architecture and Analogue Processes 8 Mental Imagery and Functional Architecture 9 Epilogue: What is Cognitive Science the Science of? (shrink)

This collection of 17 essays by the author offers a comprehensive theory of mind, encompassing traditional issues of consciousness and free will.

"Knowing how we know" is the subject of this book. Its authors present a new view of cognition that has important social and ethical implications, for, they assert, the only world we humans can have is the one we create together through the actions of our coexistence. Written for a general audience as well as for students, scholars, and scientists and abundantly illustrated with examples from biology, linguistics, and new social and cultural phenomena, this revised edition includes a new afterword (...) by Dr. Varela, in which he discusses the effect the book has had in the years since its first publication. (shrink)

Cognitivism in psychology and philosophy is roughly the position that intelligent behavior can (only) be explained by appeal to internal that is, rational thought in a very broad sense. Sections 1 to 5 attempt to explicate in detail the nature of the scientific enterprise that this intuition has inspired. That enterprise is distinctive in at least three ways: It relies on a style of explanation which is different from that of mathematical physics, in such a way that it is not (...) basically concerned with quantitative equational laws; the states and processes with which it deals are in the sense that they are regarded as meaningful or representational; and it is not committed to reductionism, but is open to reduction in a form different from that encountered in other sciences. Spelling these points out makes it clear that the Cognitivist study of the mind can be rigorous and empirical, despite its unprecedented theoretical form. The philosophical explication has another advantage as well: It provides a much needed framework for articulating questions about whether the Cognitivist approach is right or wrong. The last three sections take that advantage of the account, and address several such questions, pro and con. (shrink)

Intentionality is characteristic of many psychological phenomena. It is commonly held by philosophers that intentionality cannot be ascribed to purely physical systems. This view does not merely deny that psychological language can be reduced to physiological language. It also claims that the appropriateness of some psychological explanation excludes the possibility of any underlying physiological or causal account adequate to explain intentional behavior. This is a thesis which I do not accept. I shall argue that physical systems of a specific sort (...) will show the characteristic features of intentionality. Psychological subjects are, under an alternative description, purely physical systems of a certain sort. The intentional description and the physical description are logically distinct, and are not intertranslatable. Nevertheless, the features of intentionality may be explained by a purely causal account, in the sense that they may be shown to be totally dependent upon physical processes. (shrink)

The introduction of connectionist or parallel distributed processing (PDP) systems to model cognitive functions has raised the question of the possible relations between these models and traditional information processing models which employ rules to manipulate representations. After presenting a brief account of PDP models and two ways in which they are commonly interpreted by those seeking to use them to explain cognitive functions, I present two ways one might relate these models to traditional information processing models and so not totally (...) repudiate the tradition of modelling cognition through systems of rules and representations. The proposal that seems most promising is that PDP-type structures might provide the underlying framework in which a rule and representation model might be implemented. To show how one might pursue such a strategy, I discuss recent research by Barsalou on the instability of concepts and show how that might be accounted for in a system whose microstructure had a PDP architecture. I also outline how adopting a multi-leveled view of the mind, where on one level the mind employed a PDP-type system and at another level constituted a rule processing system, would allow researchers to relocate some problems which seemed difficult to explain at one level, such as the capacity for concept learning, to another level where it could be handled in a straightforward manner. (shrink)

Abstract A survey of different senses of the term ?representation? is presented. The presentation is guided by the appraisal that this key term is employed in the cognitive literature in different senses and that the distinction between these is not always explicitly stated or appreciated. Furthermore, the different senses seem to be associated with different rationales for the postulation of representation. Given that there may be a lack of convergence between the various senses of the construct in question and the (...) rationales for its postulation, a clear differentiation of these may be crucial for any evaluation of the role of representations in cognition and in cognitive theory. (shrink)