Common Sense, Reasoning, and Rationality by Renee Elio

By Renee Elio

Because the 11th quantity within the New instructions in Cognitive technological know-how sequence (formerly the Vancouver reviews in Cognitive technological know-how series), this paintings gives you terrific scholarship and interdisciplinary charm. It addresses 3 parts of present and sundry curiosity: logic, reasoning, and rationality. whereas logic and rationality usually were considered as specified positive factors in a unified cognitive map, this quantity deals novel, even paradoxical, perspectives of the connection. made out of impressive essays from amazing philosophers, it considers what constitutes human rationality, habit, and intelligence, whereas masking different components of philosophy, psychology, cognitive technological know-how, and computing device technology. certainly, this paintings is on the leading edge of cognitive study and offers to be of remarkable impact throughout various disciplines.

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The very architecture itself [is] a limitation on the agent's capabilities. (Doyle 1992, p. 14) The [human cognitive] architecture shows up through many ways, large and small. Indeed much of cognitive psychology is counting these ways—speed of processing, memory errors, linguistic slips, perceptual illusions, failures of rationality, decision making. These factors are grounded in part in the architecture. (Newell, Rosenbloom, and Laird 1993, p. 98) This focus on the properties of the cognitive architecture surfaces explicitly or implicitly in many accounts of how and why human performance falls short on those formal reasoning problems that are taken to measure rationality.

Under a probability-theory view of rationality, it is irrational to manipulate those independently known probabilities in such a way that these axioms, which ensure consistency, are violated. An economic model of rationality holds that a decision maker is in possession of independently specified preferences and utilities; rational choices are ones that maximize those utilities, given a set of preferences. Many matters arise from the use of these standards for rationality, in a practical sense, either for understanding human cognition or for designing machine intelligence (see, for example, Doyle 1992 for a thoughtful consideration of the latter issue).

20 Š architectures and the programs supported by such architectures. A crucial theoretical position is whether a given architecture can in principle support the "right programs" for optimizing reasoning on a particular task within a particular environment. If an AI practitioner believes it cannot, then that belief defines a different research agenda, that is, the search for an alternative architecture that has a different set of invariants, for which the "right programs" can be formulated and implemented.

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