The core of the language of thought program is the claim that thinking is the manipulation of symbols according to rules. Yet LOT has said little about symbol natures, and existing accounts are highly controversial. This is a major flaw at the heart of the LOT program: LOT requires an account of symbol natures to naturalize intentionality, to determine whether the brain even engages in symbol manipulations, and to understand how symbols relate to lower-level neurocomputational states. This paper provides the (...) much-needed theory of symbols, and in doing so, alters the LOT program in significant respects. (shrink)

In The Mind Doesn’t Work that Way, Jerry Fodor argues that mental representations have context sensitive features relevant to cognition, and that, therefore, the Classical Computational Theory of Mind (CTM) is mistaken. We call this the Globality Argument. This is an in principle argument against CTM. We argue that it is self-defeating. We consider an alternative argument constructed from materials in the discussion, which avoids the pitfalls of the official argument. We argue that it is also unsound and that, while (...) it is an empirical issue whether context sensitive features of mental representations are relevant to cognition, it is empirically implausible. (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)

Considering two of the main types of emotions, namely, perceptual emotions and cognitive emotions, in this paper we will examine which of them has a greater explanatory power for solving the frame problem. Additionally, we will analyze which of the main characteristics of perceptual and cognitive emotions type are appropriate when explaining how human beings determine relevance efficiently. We argue, assuming an intermediate position, that both types of emotions offer the necessary tools to explain how human beings solve the frame (...) problem. This is due, on the one hand, to the experiential/corporal character of the perceptual emotions and, on the other hand, to the relationship that cognitive emotions establish with the achievement of goals when facing a determined situation. (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)