Editorial preface to the fourth edition and modified translation -- The text of the Philosophische Untersuchungen -- Philosophische untersuchungen = Philosophical investigations -- Philosophie der psychologie, ein fragment = Philosophy of psychology, a fragment.

The claim that the human cognitive system tends to allocate resources to the processing of available inputs according to their expected relevance is at the basis of relevance theory. The main thesis of this chapter is that this allocation can be achieved without computing expected relevance. When an input meets the input condition of a given modular procedure, it gives this procedure some initial level of activation. Input-activated procedures are in competition for the energy resources that would allow them to (...) follow their full course. What determines which of the procedures in competition get sufficient resources to trigger their full operation is the dynamics of their activation. This dynamics depend both on the prior degree of mobilisation of a modular procedure and on the activation that propagates from other active modules. It is quite conceivable also that the mobilisation of some procedures has inhibitory effects on some others. The relevance-theoretic claim is that, at every instant, this dynamics of activation provides rough physiological indicators of expected relevance. The flow of energy in the system is locally regulated by these indicators. As a result, those input-procedure combinations that have the greatest expected relevance are the more likely ones to receive sufficient energy to follow their course. (shrink)

This chapter investigates the extent to which claims of massive modular organization of the mind (espoused by some members of the evolutionary psychology research program) are consistent with the main elements of the simple heuristics research program. A number of potential sources of conflict between the two programs are investigated and defused. However, the simple heuristics program turns out to undermine one of the main arguments offered in support of massive modularity, at least as the latter is generally understood by (...) philosophers. So one result of the argument will be to force us to re-examine the way in which the notion of modularity in cognitive science should best be characterized, if the thesis of massive modularity isn’t to be abandoned altogether. What is at stake in this discussion, is whether there is a well-motivated notion of ‘module’ such that we have good reason to think that the human mind must be massively modular in its organization. I shall be arguing (in the end) that there is. (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)

Among the most pervasive and fundamental assumptions in cognitive science is that the human mind (or mind-brain) is a mechanism of some sort: a physical device com- posed of functionally specifiable subsystems. On this view, functional decomposition – the analysis of the overall system into functionally specifiable parts – becomes a central project for a science of the mind, and the resulting theories of cognitive archi- tecture essential to our understanding of human psychology.

My charge in this chapter is to set out the positive case supporting massively modular models of the human mind.1 Unfortunately, there is no generally accepted understanding of what a massively modular model of the mind is. So at least some of our discussion will have to be terminological. I shall begin by laying out the range of things that can be meant by ‘modularity’. I shall then adopt a pair of strategies. One will be to distinguish some things that (...) ‘modularity’ definitely can’t mean, if the thesis of massive modularity is to be even remotely plausible. The other will be to look at some of the arguments that have been offered in support of massive modularity, discussing what notion of ‘module’ they might warrant. It will turn out that there is, indeed, a strong case in support of massively modular models of the mind on one reasonably natural understanding of ‘module’. But what really matters in the end, of course, is the substantive question of what sorts of structure are adequate to account for the organization and operations of the human mind, not whether or not the components appealed to in that account get described as ‘modules’. So the more interesting question before us is what the arguments that have been offered in support of massive modularity can succeed in showing us about those structures, whatever they get called. (shrink)

When Fodor titled his (1983) book the _Modularity of Mind_, he overstated his position. His actual view is that the mind divides into systems some of which are modular and others of which are not. The book would have been more aptly, if less provocatively, called _The Modularity of Low-Level Peripheral Systems_. High-level perception and cognitive systems are non-modular on Fodor’s theory. In recent years, modularity has found more zealous defenders, who claim that the entire mind divides into highly specialized (...) modules. This view has been especially popular among Evolutionary Psychologists. They claim that the mind is massively modular (Cosmides and Tooby, 1994; Sperber, 1994; Pinker, 1997; see also Samuels, 1998). Like a Swiss Army Knife, the mind is an assembly of specialized tools, each of which has been designed for some particular purpose. My goal here is to raise doubts about both peripheral modularity and massive modularity. To do that, I will rely on the criteria for modularity laid out by Fodor (1983). I will argue that neither input systems, nor central systems are modular on any of these criteria. (shrink)

We respect Herbert A. Simon as an established leader of empirical and logical analysis in the human sciences while we happily think of him as also the loner; of course he works with many colleagues but none can match him. He has been writing fruitfully and steadily for four decades in many fields, among them psychology, logic, decision theory, economics, computer science, management, production engineering, information and control theory, operations research, confirmation theory, and we must have omitted several. With all (...) of them, he is at once the technical scientist and the philosophical critic and analyst. When writing of decisions and actions, he is at the interface of philosophy of science, decision theory, philosophy of the specific social sciences, and inventory theory. When writing on causality, he is at the interface of methodology, metaphysics, logic and philosophy of physics, systems theory, and so on. Not that the interdisciplinary is his orthodoxy; we are delighted that he has chosen to include in this book both his early and little-appreciated treatment of straightforward philosophy of physics - the axioms of Newtonian mechanics, and also his fine papers on pure confirmation theory. (shrink)

Together, these collected papers develop the idea that human thinking - from scientific creativity to simply understanding what a positive HIV test means - "happens" partly outside the mind.".

This is the classic work upon which modern-day game theory is based. What began as a modest proposal that a mathematician and an economist write a short paper together blossomed, when Princeton University Press published Theory of Games and Economic Behavior. In it, John von Neumann and Oskar Morgenstern conceived a groundbreaking mathematical theory of economic and social organization, based on a theory of games of strategy. Not only would this revolutionize economics, but the entirely new field of scientific inquiry (...) it yielded--game theory--has since been widely used to analyze a host of real-world phenomena from arms races to optimal policy choices of presidential candidates, from vaccination policy to major league baseball salary negotiations. And it is today established throughout both the social sciences and a wide range of other sciences. (shrink)

This book explores the idea that we have two minds - one automatic, unconscious, and fast, the other controlled, conscious, and slow. It brings together leading researchers on dual-process theory to summarize the state of the art highlight key issues, present different perspectives, and provide a stimulus to further work.

Although philosophy has been only a minor contributor to cognitive science to date, this paper describes two projects in naturalistic philosophy of mind and one in naturalistic philosophy of science that have been pursued during the past 30 years and that can make theoretical and methodological contributions to cognitive science. First, stances on the mind–body problem (identity theory, functionalism, and heuristic identity theory) are relevant to cognitive science as it negotiates its relation to neuroscience and cognitive neuroscience. Second, analyses of (...) mental representations address both their vehicles and their contents; new approaches to characterizing how representations have content are particularly relevant to understanding the relation of cognitive agents to their environments. Third, the recently formulated accounts of mechanistic explanation in philosophy of science both provide perspective on the explanatory project of cognitive science and may offer normative guidance to cognitive science (e.g., by providing perspective on how multiple disciplinary perspectives can be integrated in understanding a given mechanism). (shrink)

I present the symbol grounding problem in the larger context of a materialist theory of content and then present two problems for causal, teleo-functional accounts of content. This leads to a distinction between two kinds of mental representations: presentations and symbols; only the latter are cognitive. Based on Milner and Goodale’s dual route model of vision, I posit the existence of precise interfaces between cognitive systems that are activated during object recognition. Interfaces are constructed as a child learns, and is (...) taught, how to interact with its environment; hence, interface structure has a social determinant essential for symbol grounding. Symbols are encoded in the brain to exploit these interfaces, by having projections to the interfaces that are activated by what they symbolise. I conclude by situating my proposal in the context of Harnad’s (1990) solution to the symbol grounding problem and responding to three standard objections. (shrink)

Jerry Fodor's argument for an innate language of thought continues to be a hurdle for researchers arguing that natural languages provide us with richer conceptual systems than our innate cognitive resources. I argue that because the logical/formal terms of natural languages are given a usetheory of meaning, unlike predicates, logical/formal terms might be learned without a mediating internal representation. In that case, our innate representational system might have less logical structure than a natural language, making it possible that we augment (...) our innate representational system and improve our ability to think by learning a natural language. (shrink)

This article described three heuristics that are employed in making judgements under uncertainty: representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value (...) is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty. (shrink)

How can anyone be rational in a world where knowledge is limited, time is pressing, and deep thought is often an unattainable luxury? Traditional models of unbounded rationality and optimization in cognitive science, economics, and animal behavior have tended to view decision-makers as possessing supernatural powers of reason, limitless knowledge, and endless time. But understanding decisions in the real world requires a more psychologically plausible notion of bounded rationality. In Simple heuristics that make us smart (Gigerenzer et al. 1999), we (...) explore fast and frugal heuristics – simple rules in the mind's adaptive toolbox for making decisions with realistic mental resources. These heuristics can enable both living organisms and artificial systems to make smart choices quickly and with a minimum of information by exploiting the way that information is structured in particular environments. In this précis, we show how simple building blocks that control information search, stop search, and make decisions can be put together to form classes of heuristics, including: ignorance-based and one-reason decision making for choice, elimination models for categorization, and satisficing heuristics for sequential search. These simple heuristics perform comparably to more complex algorithms, particularly when generalizing to new data – that is, simplicity leads to robustness. We present evidence regarding when people use simple heuristics and describe the challenges to be addressed by this research program. Key Words: adaptive toolbox; bounded rationality; decision making; elimination models; environment structure; heuristics; ignorance-based reasoning; limited information search; robustness; satisficing; simplicity. (shrink)

Chiappe and Kukla argue that relevance theory fails to solve the frame problem as defined by Fodor. They are right. They are wrong, however, to take Fodor’s frame problem too seriously. Fodor’s concerns, on the other hand, even though they are wrongly framed, are worth addressing. We argue that Relevance thoery helps address them.

Complex cognitive skills such as reading and calculation and complex cognitive achievements such as formal science and mathematics may depend on a set of building block systems that emerge early in human ontogeny and phylogeny. These core knowledge systems show characteristic limits of domain and task specificity: Each serves to represent a particular class of entities for a particular set of purposes. By combining representations from these systems, however human cognition may achieve extraordinary flexibility. Studies of cognition in human infants (...) and in nonhuman primates therefore may contribute to understanding unique features of human knowledge. 2020 APA, all rights reserved). (shrink)

It is often claimed that there can be no such thing as a logic of scientific discovery, but only a logic of verification. By 'logic of discovery' is usually meant a normative theory of discovery processes. The claim that such a normative theory is impossible is shown to be incorrect; and two examples are provided of domains where formal processes of varying efficacy for discovering lawfulness can be constructed and compared. The analysis shows how one can treat operationally and formally (...) phenomena that have usually been dismissed with fuzzy labels like 'intuition' and 'creativity'. (shrink)

In recent years evolutionary psychologists have developed and defended the Massive Modularity Hypothesis, which maintains that our cognitive architecture—including the part that subserves ‘central processing’ —is largely or perhaps even entirely composed of innate, domain-specific computational mechanisms or ‘modules’. In this paper I argue for two claims. First, I show that the two main arguments that evolutionary psychologists have offered for this general architectural thesis fail to provide us with any reason to prefer it to a competing picture of the (...) mind which I call the Library Model of Cognition. Second, I argue that this alternative model is compatible with the central theoretical and methodological commitments of evolutionary psychology. Thus I argue that, at present, the endorsement of the Massive Modularity Hypothesis by evolutionary psychologists is both unwarranted and unmotivated. (shrink)

In this paper I defend the classical computational account of reasoning against a range of highly influential objections, sometimes called relevance problems. Such problems are closely associated with the frame problem in artificial intelligence and, to a first approximation, concern the issue of how humans are able to determine which of a range of representations are relevant to the performance of a given cognitive task. Though many critics maintain that the nature and existence of such problems provide grounds for rejecting (...) classical computationalism, I show that this is not so. Some of these putative problems are a cause for concern only on highly implausible assumptions about the extent of our cognitive capacities, whilst others are a cause for concern only on similarly implausible views about the commitments of classical computationalism. Finally, some versions of the relevance problem are not really objections but hard research issues that any satisfactory account of cognition needs to address. I conclude by considering the diagnostic issue of why accounts of cognition in general—and classical computational accounts, in particular—have faired so poorly in addressing such research issues.Keywords: Computationalism; Frame problem; Relevance. (shrink)

In Furnishing the Mind, Jesse Prinz attempts to swing the pendulum back toward empiricism.

A defense of antecedent physicalism, which argues against the idea that if everything that goes on in the universe is physical, our consciousness and feelings ..

The now-classic Metaphors We Live By changed our understanding of metaphor and its role in language and the mind. Metaphor, the authors explain, is a fundamental mechanism of mind, one that allows us to use what we know about our physical and social experience to provide understanding of countless other subjects. Because such metaphors structure our most basic understandings of our experience, they are "metaphors we live by"--metaphors that can shape our perceptions and actions without our ever noticing them. In (...) this updated edition of Lakoff and Johnson's influential book, the authors supply an afterword surveying how their theory of metaphor has developed within the cognitive sciences to become central to the contemporary understanding of how we think and how we express our thoughts in language. (shrink)

Hans Krebs' discovery, in 1932, of the urea cycle was a major event in biochemistry. This article describes a program, KEKADA, which models the heuristics Hans Krebs used in this discovery. KEKADA reacts to surprises, formulates explanations, and carries out experiments in the same manner as the evidence in the form of laboratory notebooks and interviews indicates Hans Krebs did. Furthermore, we answer a number of questions about the nature of the heuristics used by Krebs, in particular: How domain‐specific are (...) the heuristics? To what extent are they idiosyncratic to Krebs? To what extent do they represent general strategies of problem‐solving search?The relative generality of KEKADA allows us to view the control structure of KEKADA and its domain‐independent heuristics as a model of scientific experimentation that should apply over a broad domain. (shrink)