A detailed study of scientific theories of human nature and the possible ways in which human behavior can be predicted and controlled.

Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation). The current report develops a proposal along these lines first described by Jordan (1986) which involves the use of recurrent links in order to provide networks with a dynamic memory. In this approach, hidden unit patterns are fed back to themselves: (...) the internal representations which develop thus reflect task demands in the context of prior internal states. A set of simulations is reported which range from relatively simple problems (temporal version of XOR) to discovering syntactic/semantic features for words. The networks are able to learn interesting internal representations which incorporate task demands with memory demands: indeed, in this approach the notion of memory is inextricably bound up with task processing. These representations reveal a rich structure, which allows them to be highly context‐dependent, while also expressing generalizations across classes of items. These representations suggest a method for representing lexical categories and the type/token distinction. (shrink)

Elements of Episodic Memory is a classic text in the psychology literature. It had a significant influence on research in the area has been much sought after in recent years. Finally, it has now been made available again with this reissue, the text unchanged from the original.

Attempts to indentify the fundamental concepts of language, argues that the study of language reveals hidden facts about the mind, and looks at the impact of propaganda.

This first volume contains discussions of the brain, methods for analyzing behavior, thought, consciousness, attention, association, time, and memory.

Ethologists and others studying animal behavior in a spirit are in need of a descriptive language and method that are neither anachronistically bound by behaviorist scruples nor prematurely committed to particular Just such an interim descriptive method can be found in intentional system theory. The use of intentional system theory is illustrated with the case of the apparently communicative behavior of vervet monkeys. A way of using the theory to generate data - including usable, testable data - is sketched. The (...) underlying assumptions of this approach can be seen to ally it directly with theorizing in evolutionary biology, which has recently come under attack from Stephen Gould and Richard Lewontin, who castigate it as the Their arguments, which are strongly analogous to B. F, Skinner's arguments against point to certain pitfalls that attend the careless exercise of such thinking (and rival varieties of thinking as well), but do not constitute a fundamental objection to either adaptationist theorizing or its cousin, intentional system theory. (shrink)

The central characteristic of cognitive explanations of behavior is the appeal to inner representations. I examine the grounds which justify representational explanations, seeking the minimum conditions which organisms must meet to be candidates for such explanations. I first discuss Fodor's proposal that representationality be attributed to systems which respond to nonnomic properties, arguing that the distinction between the nomic and nonnomic in perception is fatally ambiguous. Then I turn to an illustrative review of the behavior and neurobiology of Hermissenda crassicornis, (...) a marine mollusk. Concerning this "model system," I compare the representational style of explanation with both behaviorist and neurophysiological explanations. Representational explanation is potentially more comprehensive than its rivals, and thus I conclude that representations are useful posits wherever internal information-bearing states mediate behavior. (shrink)

Drawing on philosophy, neuroscience, and artificial intelligence, Simple Minds explores the construction of the mind from the matter of the brain.