This book is a definitive reference source for the growing, increasingly more important, and interdisciplinary field of computational cognitive modeling, that is, computational psychology. It combines breadth of coverage with definitive statements by leading scientists in this field. Research in computational cognitive modeling explores the essence of cognition through developing detailed, process-based understanding by specifying computational mechanisms, structures, and processes. Computational models provide both conceptual clarity and precision at the same time. This book substantiates (...) this approach through overviews and many examples. (shrink)

Intentionalism must be distinguished from computational psychology. The former is a mentalist-realist metatheoretical stance vis-a-vis the latter, which is a research programme devoted to the construction of informationally-characterized simulation models for human behavior, perception, cognition, etc. Intentionalism has its attractive aspects, but unfortunately it is plagued by severe conceptual difficulties. Recent attempts to justify the intentionalist interpretation of computational models, by J.A. Fodor and by C. Graves, J.J. Katz et al., fail to secure a conceptually adequate and (...) genuinely intentional sense for the intentional idiom they employ. (shrink)

One particularly successful approach to modeling within cognitive science is computational psychology. Computational psychology explores psychological processes by building and testing computational models with human data. In this paper, it is argued that a specific approach to understanding computation, what is called the ‘narrow conception’, has problematically limited the kinds of models, theories, and explanations that are offered within computational psychology. After raising two problems for the narrow conception, an alternative, ‘wide approach’ to (...) computational psychology is proposed. (shrink)

The aims of this paper are threefold: To show that game-playing (GP), the discipline of Artificial Intelligence (AI) concerned with the development of automated game players, has a strong epistemological relevance within both AI and the vast area of cognitive sciences. In this context games can be seen as a way of securely reducing (segmenting) real-world complexity, thus creating the laboratory environment necessary for testing the diverse types and facets of intelligence produced by computer models. This paper aims to promote (...) the belief that games represent an excellent tool for the project of computational psychology (CP). To underline how, despite this, GP has mainly adopted an engineering-inspired methodology and in doing so has distorted the framework of cognitive functionalism. Many successes (i.e. chess, checkers) have been achieved refusing human-like reasoning. The AI has appeared to work well despite ignoring an intrinsic motivation, that of creating an explanatory link between machines and mind. To assert that substantial improvements in GP may be obtained in the future only by renewed interest in human-inspired models of reasoning and in other cognitive studies. In fact, if we increase the complexity of games (from NP-Completeness to AI-Completeness) in order to reproduce real-life problems, computer science techniques enter an impasse. Many of AI’s recent GP experiences can be shown to validate this. The lack of consistent philosophical foundations for cognitive AI and the minimal philosophical commitment of AI investigation are two of the major reasons that play an important role in explaining why CP has been overlooked. (shrink)

Intentionalism must be distinguished from computational psychology. The former is a mentalist-realist metatheoretical stance vis-a-vis the latter, which is a research programme devoted to the construction of informationally-characterized simulation models for human behavior, perception, cognition, etc. Intentionalism has its attractive aspects, but unfortunately it is plagued by severe conceptual difficulties. Recent attempts to justify the intentionalist interpretation of computational models, by J.A. Fodor and by C. Graves, J.J. Katz et al., fail to secure a conceptually adequate and (...) genuinely intentional sense for the intentional idiom they employ. (shrink)

Jerry Fodor argues against the widely held view that mental processes are largely computations, that the architecture of cognition is massively modular, and...

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)

Computational psychology refers to the effort to create computational mechanisms that, in some way, mimic mechanisms within the brain. More specifically, the goal in creating these mechanisms is to show that they can systematically reproduce patterns of human behaviour elicited under specific conditions. From this it is inferred that these mechanisms bare some similarity to the brain mechanisms that produced the human behaviours. In most cases this involves mimicking the results of psychology experiments, although it is (...) good to see in this book, two chapters discussing the application of this approach to non experimental areas. (shrink)

This paper addresses a recent argument of the Churchlands against the "linguistic-rationalist" tradition exemplified by current cognitive-computational psychology. Because of its commitment to methodological solipsism--the argument goes--computational psychology cannot provide an account of how organisms are able to represent and "hook up to" the world. First I attempt to determine the exact nature of this charge and its relation to the Churchlands' long-standing polemic against 'folk psychology' and the linguistic-rationalist methodology. I then turn my attention (...) to the Churchlands' account of what it is for computational psychology to be methodologically solipsistic. I argue that there is no reason to suppose that methodological solipsism commits one to a purely syntactic theory of the mind (of the kind that Stephen Stich has recently advocated): the formality constraints that methodological solipsism imposes on psychological explanation do not exclude 'essential' reference to the representational content of mental states, as long as this content is construed in the 'narrow' sense. I conclude by raising a problem for computational psychology that may provide some real cause for concern. (shrink)

Over the last quarter century or so, no one has done more to shape debate in the philosophy of mind and cognitive science than Jerry Fodor. He is best known for championing the Computational Theory of Mind (CTM), the view that thinking consists of computations over syntactically structured mental representations (Fodor, 1975). He has also developed the idea that the mind is partially made up of isolated mechanisms called “modules” that employ innate databases informationally encapsulated from the rest of (...) the mind (Fodor, 1983). (shrink)

What is the mind? How does it work? How does it influence behavior? Some psychologists hope to answer such questions in terms of concepts drawn from computer science and artificial intelligence. They test their theories by modeling mental processes in computers. This book shows how computer models are used to study many psychological phenomena--including vision, language, reasoning, and learning. It also shows that computer modeling involves differing theoretical approaches. Computational psychologists disagree about some basic questions. For instance, should the (...) mind be modeled by digital computers, or by parallel-processing systems more like brains? Do computer programs consist of meaningless patterns, or do they embody (and explain) genuine meaning? (shrink)

The general understanding of pictorial representation as constructed through the viewpoint of the artist outside the picture space is mediated through our present-day familiarity with geometric perspective and photography. This presumes the existence of an external viewpoint. This understanding of painting has become common sense. In this way a 'historical product' has been taken as an 'a-historical essence' of our understanding. Even now, many theories on painting seem to remain caught in such a essentialist thinking. In this paper I discuss (...) the problem of essentialist thinking, basing my views on the philosophy of Kiyoshi Miki, one of the important philosophers of the 'Kyoto School', and then reexamine the belief in the existence of viewpoints outside of painting. (shrink)

The relation between computational and intentional psychology has always been a vexing issue. The worry is that if mental processes are computational, then these processes, which are defined over symbols, are sensitive solely to the non-semantic properties of symbols. If so, perhaps psychology could dispense with adverting in its laws to intentional/semantic properties of symbols. Stich, as is well-known, has made a great deal out of this tension and argued for a purely "syntactic" psychology by (...) driving a wedge between a semantic individuation of symbol tokens and their narrow functional individuation. If the latter can be carried out, he claimed, we do not need semantic typing. I argue that since a narrow functional individuation cannot type-identify symbol tokens across organisms, a semantic account of typing must be the only option given that interpersonal physical individuation of tokens is not to be taken seriously. (shrink)

This review sketches Fodor's critique of evolutionary psychology and the 'massive modularity' thesis; queries his views on abduction in central processes; and suggests that his pessimism about the scope of computational psychology undermines his realism about folk psychology.

Objections to AI and computational cognitive science are myriad. Accordingly, there are many different reasons for these attacks. But all of them come down to one simple observation: humans seem a lot smarter that computers -- not just smarter as in Einstein was smarter than I, or I am smarter than a chimpanzee, but more like I am smarter than a pencil sharpener. To many, computation seems like the wrong paradigm for studying the mind. (Actually, I think there are (...) deeper and darker reasons why AI, especially, is so often the brunt of polemics, see Dietrich, 2000.) But the truth is this: AI is making exciting progress, and will one day make a robot as intelligent as a person; indeed the robot will be conscious. And all this is because of another truth: the computational paradigm is the best thing to come down the pike since the wheel. (shrink)

Although Paul Churchland and Jerry Fodor both subscribe to the so-called theory-theory– the theory that folk psychology (FP) is an empirical theory of behavior – they disagree strongly about FP’s fate. Churchland contends that FP is a fundamentally flawed view analogous to folk biology, and he argues that recent advances in computational neuroscience and connectionist AI point toward development of a scientifically respectable replacement theory that will give rise to a new common-sense psychology. Fodor, however, wagers that (...) FP will be largely preserved and vindicated by scientific investigations of behavior. Recent findings by developmental psychologists, I argue, will push both Churchlandians and Fodorians toward the pessimistic view that FP is a misguided theory that will never be displaced, because it is, so to speak, built into our cognitive systems. I explore the possibility of preserving optimism by rejecting the theory-theory and adopting the simulation theory, a competing view developed by Robert Gordon, Alvin Goldman, and Jane Heal. According to simulationists, common-sense interpretation of behavior is accomplished by means of pretense-like operations that deploy the cognitive system’s own reasoning capabilities in a disengaged manner. Since on this view no theory-like set of principles would be needed, the simulation theory seems to enjoy a simplicity advantage over the theory-theory. Steven Stich and Shawn Nichols, however, contend that as the cognitive system would require special mechanisms for disengaged operation, the simplicity question cannot be resolved until suitable computational models are developed. I describe a set of models I have constructed to meet this need, and I discuss the contribution such models can make to determining FP’s fate. (shrink)

In this paper, I argue for a modified version of what Devitt calls the Representational Thesis. According to RT, syntactic rules or principles are psychologically real, in the sense that they are represented in the mind/brain of every linguistically competent speaker/hearer. I present a range of behavioral and neurophysiological evidence for the claim that the human sentence processing mechanism constructs mental representations of the syntactic properties of linguistic stimuli. I then survey a range of psychologically plausible computational models of (...) comprehension and show that they are all committed to RT. I go on to sketch a framework for thinking about the nature of the representations involved in sentence processing. My claim is that these are best characterized not as propositional attitudes but, rather, as subpersonal states whose representational properties are determined by their functional role. Finally, I distinguish between explicit and implicit representations and argue that the latter can be drawn on as data by the algorithms that constitute our sentence processing routines. I conclude that skepticism concerning the psychological reality of grammars cannot be sustained. (shrink)

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)

Reading psychology is an important basis for formulating news strategies. The purpose of this paper is to study how to analyze and study the psychological mechanism of reading and news communication strategies based on affective computing. It described the conditional random field. This paper put forward the problem of affective computing, which is based on affective computing technology. Then it expounded the concept of conditional random fields and related algorithms, and designed and analyzed cases of news communication strategies. Through (...) the period from April 1, 2022 to June 1, 2022, the 300 short videos of news and information with the highest playback volume respectively released by Z software were used as research samples, and a multi-angle analysis was carried out. Among the 300 selected news information videos, 252 videos are original content, accounting for 84.00%, and the other short videos are from the self-media of the platform. At present, it is necessary to continuously develop intelligent products that meet the needs of users at different stages, and carry out personalized design in strict accordance with the living habits and natural conditions of different groups of people. Then continuously improving the experience of different groups of people using new media products, so that their reading interest can be more effectively stimulated. (shrink)

Understanding causal structure is a central task of human cognition. Causal learning underpins the development of our concepts and categories, our intuitive theories, and our capacities for planning, imagination and inference. During the last few years, there has been an interdisciplinary revolution in our understanding of learning and reasoning: Researchers in philosophy, psychology, and computation have discovered new mechanisms for learning the causal structure of the world. This new work provides a rigorous, formal basis for theory theories of concepts (...) and cognitive development, and moreover, the causal learning mechanisms it has uncovered go dramatically beyond the traditional mechanisms of both nativist theories, such as modularity theories, and empiricist ones, such as association or connectionism. (shrink)

The paper criticizes standard functionalist arguments for multiple realization. It focuses on arguments in which psychological states are conceived as computational, which is precisely where the multiple realization doctrine has seemed the strongest. It is argued that a type-type identity thesis between computational states and physical states is no less plausible than a multiple realization thesis. The paper also presents, more tentatively, positive arguments for a picture of local reduction.

The past three decades have witnessed a remarkable growth of research interest in the mind. This trend has been acclaimed as the ‘cognitive revolution’ in psychology. At the heart of this revolution lies the claim that the mind is a computational system. The purpose of this paper is both to elucidate this claim and to evaluate its implications for cognitive psychology. The nature and scope of cognitive psychology and cognitive science are outlined, the principal assumptions underlying (...) the information processing approach to cognition are summarised and the nature of artificial intelligence and its relationship to cognitive science are explored. The ‘computational metaphor’ of mind is examined and both the theoretical and methodological issues which it raises for cognitive psychology are considered. Finally, the nature and significance of ‘connectionism’—the latest paradigm in cognitive science—are briefly reviewed. (shrink)