Cognitive modules are internal mental structures. Some theorists and empirical researchers hypothesise that the human mind is either partially or massively comprised of structures that are modular in nature. Is the massive modularity of mind hypothesis a cogent view about the ontological nature of human mind or is it, rather, an effective/ineffective adaptationist discovery heuristic for generating predictively successful hypotheses about both heretofore unknown psychological traits and unknown properties of already identified psychological traits? Considering the inadequacies of the case in (...) favour of massive modularity as an ontological hypothesis, I suggest approaching and valuing massive modularity as an adaptationist discovery heuristic. (shrink)

As many philosophers agree, the frame problem is concerned with how an agent may efficiently filter out irrelevant information in the process of problem-solving. Hence, how to solve this problem hinges on how to properly handle semantic relevance in cognitive modeling, which is an area of cognitive science that deals with simulating human's cognitive processes in a computerized model. By "semantic relevance", we mean certain inferential relations among acquired beliefs which may facilitate information retrieval and practical reasoning under certain epistemic (...) constraints, e. g., the insufficiency of knowledge, the limitation of time budget, etc. However, traditional approaches to relevance—as for example, relevance logic, the Bayesian approach, as well as Description Logic—have failed to do justice to the foregoing constraints, and in this sense, they are not proper tools for solving the frame problem/relevance problem. As we will argue in this paper, Non-Axiomatic Reasoning System (NARS) can handle the frame problem in a more proper manner, because the resulting solution seriously takes epistemic constraints on cognition as a fundamental theoretical principle. (shrink)

The frame problem is the difficulty of explaining how non-magical systems think and act in ways that are adaptively sensitive to context-dependent relevance. Influenced centrally by Heideggerian phenomenology, Hubert Dreyfus has argued that the frame problem is, in part, a consequence of the assumption (made by mainstream cognitive science and artificial intelligence) that intelligent behaviour is representation-guided behaviour. Dreyfus' Heideggerian analysis suggests that the frame problem dissolves if we reject representationalism about intelligence and recognize that human agents realize the property (...) of thrownness (the property of being always already embedded in a context). I argue that this positive proposal is incomplete until we understand exactly how the properties in question may be instantiated in machines like us. So, working within a broadly Heideggerian conceptual framework, I pursue the character of a representation-shunning thrown machine. As part of this analysis, I suggest that the frame problem is, in truth, a two-headed beast. The intra-context frame problem challenges us to say how a purely mechanistic system may achieve appropriate, flexible and fluid action within a context. The inter-context frame problem challenges us to say how a purely mechanistic system may achieve appropriate, flexible and fluid action in worlds in which adaptation to new contexts is open-ended and in which the number of potential contexts is indeterminate. Drawing on the field of situated robotics, I suggest that the intra-context frame problem may be neutralized by systems of special-purpose adaptive couplings, while the inter-context frame problem may be neutralized by systems that exhibit the phenomenon of continuous reciprocal causation. I also defend the view that while continuous reciprocal causation is in conflict with representational explanation, special-purpose adaptive coupling, as well as its associated agential phenomenology, may feature representations. My proposal has been criticized recently by Dreyfus, who accuses me of propagating a cognitivist misreading of Heidegger, one that, because it maintains a role for representation, leads me seriously astray in my handling of the frame problem. I close by responding to Dreyfus' concerns. (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.

ABSTRACT: Brandom argues that functionalism must ultimately fail because it will not be able to explain how we can holistically update our beliefs solely in terms of abilities possessed by non-linguistic things. In this paper I respond to this argument by arguing that non-linguistic animals encounter and overcome an analogous sort of holistic updating problem. I will also try to demystify holism and de-intellectualize language use/reasoning.

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)

How can abductive reasoning be physical, feasible, and reliable? This is Fodor’s riddle of abduction, and its apparent intractability is the cause of Fodor’s recent pessimism regarding the prospects for cognitive science. I argue that this riddle can be solved if we augment the computational theory of mind to allow for non-computational mental processes, such as those posited by classical associationists and contemporary connectionists. The resulting hybrid theory appeals to computational mechanisms to explain the semantic coherence of inference and associative (...) mechanisms to explain the efficient retrieval of relevant information from memory. The interaction of these mechanisms explains how abduction can be physical, feasible, and reliable. (shrink)

In The Elm and the Expert (1994), Fodor attempts to reconcile the idea that psychological laws are characteristically intentional with the idea that their implementation is typically computational. In order to do so, Fodor must show that narrow contents are superfluous for the purposes of psychological explanation and that Frege cases are rare and constitute unsystematic exceptions. The paper contends that the argument Fodor offers in order to establish his claim is flawed. It argues that the principle of informational equilibrium (...) the argument is based on rests on an utterly implausible conception of the rationality of action. (shrink)

Inquiry, Volume 57, Issue 1, Page 55-96, February 2014.

The frame problem is widely reputed among philosophers to be one of the deepest and most difficult problems of cognitive science. This paper discusses three recent attempts to display this problem: Dennett's problem of ignoring obviously irrelevant knowledge, Haugeland's problem of efficiently keeping track of salient side effects, and Fodor's problem of avoiding the use of kooky concepts. In a negative vein, it is argued that these problems bear nothing but a superficial similarity to the frame problem of AI, so (...) that they do not provide reasons to disparage standard attempts to solve it. More positively, it is argued that these problems are easily solved by slight variations on familiar AI themes. Finally, some discussion is devoted to more difficult problems confronting AI. (shrink)

We begin to fill a lacuna in the relevance logic enterprise by providing a foundational analysis of identity in relevance logic. We consider rival interpretations of identity in this context, settling on the relevant indiscernibility interpretation, an interpretation related to Dunn's relevant predication project. We propose a general test for the stability of an axiomatisation of identity, relative to this interpretation, and we put various axiomatisations to this test. We fill our discussion out with both formal and philosophical remarks on (...) identity in relevance logic. (shrink)

Unlike human soldiers, autonomous weapons systems are unaffected by psychological factors that would cause them to act outside the chain of command. This is a compelling moral justification for their development and eventual deployment in war. To achieve this level of sophistication, the software that runs AWS will have to first solve two problems: the frame problem and the representation problem. Solutions to these problems will inevitably involve complex software. Complex software will create security risks and will make AWS critically (...) vulnerable to hacking. I claim that the political and tactical consequences of hacked AWS far outweigh the purported advantages of AWS not being affected by psychological factors and always following orders. Therefore, one of the moral justifications for the deployment of AWS is undermined. (shrink)

Cognitive science's basic premises are under attack. In particular, its focus on internal cognitive processes is a target. Intelligence is increasingly interpreted, not as a matter of reclusive thought, but as successful agent-environment interaction. The critics claim that a major reorientation of the field is necessary. However, this will only occur when there is a distinct alternative conceptual framework to replace the old one. Whether or not a serious alternative is provided is not clear. Among the critics there is some (...) consensus, however, that this role could be fulfilled by the concept of a 'behavioral system'. This integrates agent and environment into one encompassing general system. We will discuss two contexts in which the behavioral systems idea is being developed. Autonomous Agents Research is the enterprise of building behavior-based robots. Dynamical Systems Theory provides a mathematical framework well suited for describing the interactions between complex systems. We will conclude that both enterprises provide important contributions to the behavioral systems idea. But neither turns it into a full conceptual alternative which will initiate a major paradigm switch in cognitive science. The concept will need a lot of fleshing out before it can assume that role. (shrink)

Two long-standing arguments in cognitive science invoke the assumption that holistic inference is computationally infeasible. The first is Fodor’s skeptical argument toward computational modeling of ordinary inductive reasoning. The second advocates modular computational mechanisms of the kind posited by Cosmides, Tooby and Sperber. Based on advances in machine learning related to Bayes nets, as well as investigations into the structure of scientific and ordinary information, I maintain neither argument establishes its architectural conclusion. Similar considerations also undermine Fodor’s decades-long diagnosis of (...) artificial intelligence research as confounded by an inability to circumscribe the amount of information relevant to inferential processes. This diagnosis is particularly inapposite with respect to Bayes nets, since one of their strengths as machine learning systems has been their capacity to reason probabilistically about large data sets whose size overwhelms the capacities of individual human reasoners. A general moral follows from these criticisms: Insights into artificial and human cognitive systems are likely to be cultivated by focusing greater attention on the structure and density of connections among items of information that are available to them. (shrink)

Many philosophers and psychologists now argue that emotions play a vital role in reasoning. This paper explores one particular way of elucidating how emotions help reason which may be dubbed ?the search hypothesis of emotion?. After outlining the search hypothesis of emotion and dispensing with a red herring that has marred previous statements of the hypothesis, I discuss two alternative readings of the search hypothesis. It is argued that the search hypothesis must be construed as an account of what emotions (...) typically do, rather than as a definition of emotion. Even as an account of what emotions typically do, the search hypothesis can only be evaluated in the context of a specific theory of what emotions are. 1 Introduction 2 The search hypothesis of emotion 3 A red herring: the frame problem 4 The search problem 5 Two readings of the search hypothesis 6 Two final remarks 7 Conclusion. (shrink)

This paper examines three cases of the clash between science and philosophy: Zeno’s paradoxes, the Frame Problem, and a recent attempt to experimentally refute skepticism. In all three cases, the relevant science claims to have resolved the purported problem. The sciences, construing the term broadly, are mathematics, artificial intelligence, and psychology. The goal of this paper is to show that none of the three scientific solutions work. The three philosophical problems remain as vibrant as ever in the face of robust (...) scientific attempts to dispel them. The paper concludes by examining some consequences of this persistence. (shrink)

This paper examines three cases of the clash between science and philosophy: Zeno’s paradoxes, the Frame Problem, and a recent attempt to experimentally refute skepticism. In all three cases, the relevant science claims to have resolved the purported problem. The sciences, construing the term broadly, are mathematics, artificial intelligence, and psychology. The goal of this paper is to show that none of the three scientific solutions work. The three philosophical problems remain as vibrant as ever in the face of robust (...) scientific attempts to dispel them. The paper concludes by examining some consequences of this persistence. (shrink)

The implicit-explicit distinction is applied to knowledge representations. Knowledge is taken to be an attitude towards a proposition which is true. The proposition itself predicates a property to some entity. A number of ways in which knowledge can be implicit or explicit emerge. If a higher aspect is known explicitly then each lower one must also be known explicitly. This partial hierarchy reduces the number of ways in which knowledge can be explicit. In the most important type of implicit knowledge, (...) representations merely reflect the property of objects or events without predicating them of any particular entity The dearest cases of explicit knowledge of a fact are representations of one's own attitude of knowing that fact. These distinctions are discussed in their relationship to similar distinctions such as procedural-declarative, conscious unconscious, verbalizable-nonverbalizable, direct-indirect tests, and automatic voluntary control. This is followed by an outline of how these distinctions can be used to integrate and relate the often divergent uses of the implicit-explicit distinction in different research areas. We illustrate this for visual perception, memory, cognitive development, and artificial grammar learning. (shrink)

In modern societies entrepreneurship and innovation are widely seen as key sources of economic growth and welfare increases. Yet entrepreneurial innovation has also meant losses and hardships for some members of society: it is destructive of some stakeholders’ wellbeing even as it creates new wellbeing among other stakeholders. Both the positive benefits and negative externalities of innovation are problematic because entrepreneurs initiate new ventures before their private profitability and/or social costs can be fully recognized. In this paper we consider three (...) analytical frameworks within which these issues might be examined: pre-commitments, contractarianism, and an entrepreneurial framework. We conclude that the intersection of stakeholder theory and entrepreneurial innovation is a potentially rich arena for research. (shrink)

Jerry Fodor argues that the massive modularity thesis – the claim that (human) cognition is wholly served by domain specific, autonomous computational devices, i.e., modules – is a priori incoherent, self-defeating. The thesis suffers from what Fodor dubs the input problem: the function of a given module (proprietarily understood) in a wholly modular system presupposes non-modular processes. It will be argued that massive modularity suffers from no such a priori problem. Fodor, however, also offers what he describes as a really (...) real input problem (i.e., an empirical one). It will be suggested that this problem is real enough, but it does not selectively strike down massive modularity – it is a problem for everyone. (shrink)

The frame problem was originally a problem for Artificial Intelligence, but philosophers have interpreted it as an epistemological problem for human cognition. As a result of this reinterpretation, however, specifying the frame problem has become a difficult task. To get a better idea of what the frame problem is, how it gives rise to more general problems of relevance, and how deep these problems run, I expound six guises of the frame problem. I then assess some proposed heuristic solutions to (...) the frame problem; I show that these proposals misunderstand, and fail to address, an important aspect of the frame problem. Finally, I argue that though human cognition does not solve the frame problem in its epistemological guise, human cognition avoids some of the epistemological worries. (shrink)

Fodor argued that in contrast to input systems which are informationally encapsulated, general intelligence is unencapsulated and hence non-modular; for this reason, he suggested, prospects for understanding it are not bright. It is argued that an additional property, primitive functionality, is required for non-modularity. A functionally primitive computational model for quantifier scoping, limited to some scoping influences, is then motivated, and an implementation described. It is argued that only such a model can be faithful to intuitive scope preferences. But it (...) is also argued that an extended model which includes all scoping influences is a hopeless prospect from a developmental perspective. Fodor's views are concluded to have some independent support: quantifier scoping is a mental ability parasitic on general intelligence that is non-modular though in a revised sense, warranting pessimism about our ability of model it. (shrink)

Sperber and Wilson (1987) have criticised Fodor's (1983) pessimistic view about the possibility of a science of central systems. Fodor's pessimism stems from the holistic nature of central systems – people can access anything that they know when engaging in belief fixation. It is argued that Sperber and Wilsons theory of how relevance is realized during verbal comprehension fails to elucidate this crucial aspect of central processes. Their claims about how a context is selected are shown to presuppose the ability (...) to realize relevance. (shrink)

The Frame Problem originated as an obstacle for classical, symbolic A.I. that was adopted, expanded, and reformulated by philosophers. The version of the problem that I focus on, the Holism Problem, points out the difficulty in programming systems to recognize and consider mostly relevant information, given that relevance is context-sensitive. My goal in this thesis is to determine whether the Global Workspace Theory (GWT) can solve the holism problem. GWT proposes that distributed parallel processing, global broadcast, and chaotic itinerancy can (...) solve the problem by providing a system with 1) the speed to search through information, 2) access to the information it needs to compute relevance, 3) the ability to synthesize information. I argue that GWT fails to enable a system to recognize any relevant information because it inadequately responds to the Epistemological Holism Problem, which requires successfully determining the norms by which a system can recognize relevance. (shrink)

Heuristics are often invoked in the philosophical, psychological, and cognitive science literatures to describe or explain methodological techniques or "shortcut" mental operations that help in inference, decision-making, and problem-solving. Yet there has been surprisingly little philosophical work done on the nature of heuristics and heuristic reasoning, and a close inspection of the way(s) in which "heuristic" is used throughout the literature reveals a vagueness and uncertainty with respect to what heuristics are and their role in cognition. This dissertation seeks to (...) remedy this situation by motivating philosophical inquiry into heuristics and heuristic reasoning, and then advancing a theory of how heuristics operate in cognition. I develop a positive working characterization of heuristics that is coherent and robust enough to account for a broad range of phenomena in reasoning and inference, and makes sense of empirical data in a systematic way. I then illustrate the work this characterization does by considering the sorts of problems that many philosophers believe heuristics solve, namely those resulting from the so-called frame problem. Considering the frame problem motivates the need to gain a better understanding of how heuristics work and the cognitive structures over which they operate. I develop a general theory of cognition which I argue underwrites the heuristic operations that concern this dissertation. I argue that heuristics operate over highly organized systems of knowledge, and I offer a cognitive architecture to accommodate this view. I then provide an account of the systems of knowledge that heuristics are supposed to operate over, in which I suggest that such systems of knowledge are concepts. The upshot, then, is that heuristics operate over concepts. I argue, however, that heuristics do not operate over conceptual content, but over metainformational relations between activated and primed concepts and their contents. Finally, to show that my thesis is empirically adequate, I consider empirical evidence on heuristic reasoning and argue that my account of heuristics explains the data. (shrink)

People cannot contemplate a proposition without believing that proposition. A model of belief fixation is sketched and used to explain hitherto disparate, recalcitrant, and somewhat mysterious psychological phenomena and philosophical paradoxes. Toward this end I also contend that our intuitive understanding of the workings of introspection is mistaken. In particular, I argue that propositional attitudes are beyond the grasp of our introspective capacities. We learn about our beliefs from observing our behavior, not from introspecting our stock beliefs. -/- The model (...) of belief fixation offered in the dissertation poses a novel dilemma for theories of rationality. One might have thought that the ability to contemplate ideas while withholding assent is a necessary condition on rationality. In short, it seems that rational creatures shouldn‘t just form their beliefs based on whatever they happen to think. However, it seems that we are creatures that automatically and reflexively form our beliefs based on whatever propositions we happen to consider. Thus, either the rational requirement that states that we must have evidence for our beliefs must be jettisoned or we must accept the conclusion that we are necessarily irrational. (shrink)

Hubert Dreyfus has argued recently that the frame problem, discussion of which has fallen out of favour in the AI community, is still a deal breaker for the majority of AI projects, despite the fact that the logical version of it has been solved. (Shanahan 1997, Thielscher 1998). Dreyfus thinks that the frame problem will disappear only once we abandon the Cartesian foundations from which it stems and adopt, instead, a thoroughly Heideggerian model of cognition, in particular one that does (...) not appeal to representations. I argue that Dreyfus is too hasty in his condemnation of all representational views; the argument he provides licenses only a rejection of disembodied models of cognition. In casting his net too broadly, Dreyfus circumscribes the cognitive playing field so closely that one is left wondering how his Heideggerian alternative could ever provide a foundation explanatorily robust enough for a theory of cognition. As a consequence, he dilutes the force of his legitimate conclusion, that disembodied cognitive models will not work, and this conclusion needs to be heard. By disentangling the ideas of embodiment and representation, at least with respect to Dreyfus‘ frame problem argument, the real locus of the general polemic between traditional computational/representational cognitive science and the more recent embodied approaches is revealed. From this, I hope that productive debate will ensue. (shrink)

It is shown that the Fodor's interpretation of the frame problem is the central indication that his version of the Modularity Thesis is incompatible with computationalism. Since computationalism is far more plausible than this thesis, the latter should be rejected.