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)

Computationalism has been the mainstream view of cognition for decades. There are periodic reports of its demise, but they are greatly exaggerated. This essay surveys some recent literature on computationalism. It concludes that computationalism is a family of theories about the mechanisms of cognition. The main relevant evidence for testing it comes from neuroscience, though psychology and AI are relevant too. Computationalism comes in many versions, which continue to guide competing research programs in philosophy of mind as well as psychology (...) and neuroscience. Although our understanding of computationalism has deepened in recent years, much work in this area remains to be done. (shrink)

During the past several decades, many epistemologists have argued for and contributed to a paradigm shift according to which knowledge is central to assertion, action, and interaction. This general position stands in sharp contrast to several recently developed accounts regarding specific epistemic contexts. These specific accounts resist applying traditional epistemic norms, including strong knowledge norms, to real-world situations of interest. In particular, I consider recent arguments about the epistemic standards for scientific pronouncements, expert testimony in a political context, and interactive (...) reasoning. I argue, firstly, that knowledge does have a crucial role to play in each case, contrary to appearances. Clarifying the role of knowledge fills gaps in our understanding left open by the existing accounts. Secondly, I show that combining the insights from the knowledge-centric approach and from the more specific accounts provides a new perspective on the open problem of developing an account of knowledge-based decisions. Specifically, I argue that the biggest open problem regarding knowledge-based decisions is not how we respond to uncertainty, but rather how we assess the relevance of our many disparate pieces of knowledge, choosing which to integrate, and how. A strong case emerges for a procedural solution to this part of the problem of how to make knowledge-based decisions. (shrink)

A basic deep neural network (DNN) is trained to exhibit a large set of input–output dispositions. While being a good model of the way humans perform some tasks automatically, without deliberative reasoning, more is needed to approach human‐like artificial intelligence. Analysing recent additions brings to light a distinction between two fundamentally different styles of computation: content‐specific and non‐content‐specific computation (as first defined here). For example, deep episodic RL networks draw on both. So does human conceptual reasoning. Combining the two takes (...) advantage of the complementary costs and benefits of each. It also offers a better model of human cognitive competence. (shrink)

Many compelling examples have recently been provided in which people can achieve impressive epistemic success, e.g. draw highly accurate inferences, by using simple heuristics and very little information. This is possible by taking advantage of the features of the environment. The examples suggest an easy and appealing naturalization of rationality: on the one hand, people clearly can apply simple heuristics, and on the other hand, they intuitively ought do so when this brings them high accuracy at little cost.. The ‘ought-can’ (...) principle is satisfied, and rationality is meaningfully normative. We show, however, that this naturalization program is endangered by a computational wrinkle in the adaptation process taken to be responsible for this heuristics-based (‘ecological’) rationality: for the adaptation process to guarantee even minimal rationality, it requires astronomical computational resources, making the problem intractable. We consider various plausible auxiliary assumptions in attempt to remove this obstacle, and show that they do not succeed; intractability is a robust property of adaptation. We discuss the implications of our findings for the project of naturalizing rationality. (shrink)

This thesis contributes to a better conceptual understanding of how self-organized control works. I begin by analyzing the control problem and its solution space. I argue that the two prominent solutions offered by classical cognitive science (centralized control with rich commands, e.g., the Fodorian central systems) and embodied cognitive science (distributed control with simple commands, such as the subsumption architecture by Rodney Brooks) are merely two positions in a two-dimensional solution space. I outline two alternative positions: one is distributed control (...) with rich commands, defended by proponents of massive modularity hypothesis; the other is centralized control with simple commands. My goal is to develop a hybrid account that combines aspects of the second alternative position and that of the embodied cognitive science (i.e., centralized and distributed controls with simple commands). Before developing my account, I discuss the virtues and challenges of the first three. This discussion results in a set of criteria for successful neural control mechanisms. Then, I develop my account through analyzing neuroscientific models of decision-making and control with the theoretical lenses provided by formal decision and social choice theories. I contend that neural processes can be productively modeled as a collective of agents, and neural self-organization is analogous to democratic self-governance. In particular, I show that the basal ganglia, a set of subcortical structures, contribute to the production of coherent and intelligent behaviors through implementing “democratic" procedures. Unlike the Fodorian central system—which is a micro-managing “neural commander-in-chief”—the basal ganglia are a “central election commission.” They delegate control of habitual behaviors to other distributed control mechanisms. Yet, when novel problems arise, they engage and determine the result on the basis of simple information (the votes) from across the system with the principles of neurodemocracy, and control with simple commands of inhibition and disinhibition. By actively managing and taking advantage of the wisdom-of-the-crowd effect, these democratic processes enhance the intelligence and coherence of the mind’s final "collective" decisions. I end by defending this account from both philosophical and empirical criticisms and showing that it meets the criteria for successful solution. (shrink)

I defend the claim that it is possible for thoughts to be context-sensitive. Assuming that a thought is a sentence of Mentalese and content is a function from indices to truth-values, then a thought, T, is context-sensitive IFF at least one of the following three conditions are met: T exhibits character-underdeterminacy, where T is character underdetermined iff a component of T makes an explicit reference to the context to establish content. T exhibits type-underdeterminacy, where T is type underdetermined iff there (...) are tokens of T that have distinct truth-values. T is token-underdetermined, where T is token underdetermined iff for some possible states of affairs its truth-value is indeterminate. Additionally, there must be a mechanism by which the content of T can be determined by appeal to the context. Otherwise T is not sensitive to the context. The most significant objection to the possibility of context-sensitive thoughts comes from a regress argument. The concern is that any process of removing context-sensitivity from a thought will token an additional thought. If that further thought is context-sensitive, then another thought will have to be tokened. This process will only terminate when a non-context-sensitive thought is arrived at. Yet this seems to show that context-sensitivity in thought, if possible, can only be a contingent, detachable feature of thoughts. To counter this argument, I will present three versions of context-sensitive thought, mirroring each of -. These views make use of a range of relationships between thoughts and their contents or extensions that are affected by the context, but I will argue they do not require the generation of an additional thought. This provides a range of views on which thoughts can be treated as essentially context-sensitive. (shrink)

This paper addresses the extent to which quotidian cognition is like scientific inference by focusing on Jerry Fodor's famous analogy. I specifically consider and rebut a recent attempt made by Tim Fuller and Richard Samuels to deny the usefulness of Fodor's analogy. In so doing, I reveal some subtleties of Fodor's arguments overlooked by Fuller and Samuels and others. Recognizing these subtleties provides a richer appreciation of the analogy, allowing us to gain better traction on the issue concerning the extent (...) to which everyday cognition is like scientific inference. In the end, I propose that quotidian cognition is indeed like scientific inference, but not precisely in the way Fodor claims it is. (shrink)

The Hard Question of memory is the following: how are memory representations stored and organized so as to be made available for retrieval in the appropriate circumstances and format? In this essay, I argue that philosophical theories of memory should engage with the Hard Question directly and seriously. I propose that declarative memory is a faculty performing a kind of cognitive triage: management of information for a variety of uses under significant computational constraints. In such triage, memory representations are preferentially (...) selected and stabilized, but also systematically modified and integrated into generalized, model-like representational structures. Further, I propose a hybrid theory of remembering, which takes into account both the nature of the cognitive processes underlying remembering and the norms that govern representational success in relevant cognitive/epistemic contexts. (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)

Do accounts of scientific theory formation and revision have implications for theories of everyday cognition? We maintain that failing to distinguish between importantly different types of theories of scientific inference has led to fundamental misunderstandings of the relationship between science and everyday cognition. In this article, we focus on one influential manifestation of this phenomenon which is found in Fodor's well-known critique of theories of cognitive architecture. We argue that in developing his critique, Fodor confounds a variety of distinct claims (...) about the holistic nature of scientific inference. Having done so, we outline more promising relations that hold between theories of scientific inference and ordinary cognition. (shrink)

The Language of Thought: A New Philosophical Direction, by SchneiderSusan. Cambridge, MA: MIT Press, 2011. Pp. xii + 259.

A fundamental task for any prospective cognitive architecture is information control: routing information to the relevant mechanisms to support a variety of tasks. Jerry Fodor has argued that the Massive Modularity Hypothesis cannot account for flexible information control due to its architectural commitments and its reliance on heuristic information processing. I argue instead that the real trouble lies in its commitment to nativism—recent massive modularity models, despite incorporating mechanisms for learning and self-organization, still cannot learn to control information flexibly enough. (...) After defending this position, I close the paper by discussing wider implications for control and cognitive architecture. (shrink)

Se ha propuesto el uso de heurísticas como una herramienta para solucionar el problema de marco. Los objetivos de este trabajo son proveer una clarificación de la literatura filosófica sobre el tema e intentar resolver los debates pendientes considerando la evidencia empírica disponible. Luego de distinguir varios aspectos del problema de marco, analizaremos las disputas filosóficas sobre el tema. A continuación comentaremos la literatura sobre la evidencia empírica relevante proveniente de la psicología cognitiva. Argumentaremos que las heurísticas pueden ser útiles (...) para solucionar sólo un aspecto del problema de marco, aun con varias restricciones. (shrink)