Artificial Believers: The Ascription of Belief

Artificial Believers: The Ascription of Belief

Artificial Believers: The Ascription of Belief

Artificial Believers: The Ascription of Belief

Synopsis

Modeling of individual beliefs is essential to the computer understanding of natural languages. Phenomena at all levels -- syntactic, semantic, and pragmatic -- cannot be fully analyzed in the absence of models of a hearer and of the hearer's model of other believers. The heart of this text is the presentation of an artificial intelligence (AI) program intended to simulate certain aspects of a human believer. This book provides a prolog program, Viewgen, that maintains belief structures about the world and other believers, and is able to ascribe beliefs to others without direct evidence by using a form of default reasoning. The authors contend that a plausible model such as this can -- in the best cognitive science tradition -- shed light on the long-standing philosophical problem of what belief is.

The issues presented here will be of considerable interest to an informed general reader as well as those with a background in any of the disciplines that make up what is now called cognitive science: philosophy, linguistics, psychology, neuropsychology, and also AI itself.

Excerpt

A word of warning may be appropriate here, so that readers can decide where to begin the book, depending on their experience of, and interest in, the issues we discuss. The heart of the book is the presentation of an artificial intelligence (AI) program intended to simulate certain aspects of a human believer. We present it as painlessly as possible, but the account is technical in parts as it must be if it is to meet the normal standards of a monograph in artificial intelligence.

The technical core of this work is a prolog program Viewgen, one that maintains belief structures about the world and other believers, and is able to ascribe beliefs to others without direct evidence by using a form of default reasoning, a notion that we shall explain shortly. A further claim is that the structures, and associated reasoning, we propose also have consequences for identifying alternative descriptions of entities and for notions such as metaphor and speech acts. We argue that representational issues that have traditionally been considered as very different can be seen as closely related.

We believe the issues presented here are of considerable interest to an informed general reader and anyone with a background in any of the disciplines that make up what is nowadays called cognitive science: philosophy, linguistics, psychology, perhaps even neurophysiology, as well as AI itself, which constitutes the anchor subject of cognitive science, and the one that provides the key computational metaphor for mental processes.

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