COMPUTER THOUGHT: PROPOSITIONAL ATTITUDES AND META-KNOWLEDGE (ARTIFICIAL INTELLIGENCE, SEMANTICS, PSYCHOLOGY, ALGORITHMS).

摘要

Though artificial intelligence scientists frequently use words such as "belief" and "desire" when describing the computational capacities of their programs and computers, they have completely ignored the philosophical and psychological theories of belief and desire. Hence, their explanations of computational capacities which use these terms are frequently little better than folk-psychological explanations. Conversely, though philosophers and psychologists attempt to couch their theories of belief and desire in computational terms, they have consistently misunderstood the notions of computation and computational semantics. Hence, their theories of such attitudes are frequently inadequate. A computational theory of propositional attitudes (belief and desire) is presented here. It is argued that the theory of propositional attitudes put forth by philosophers and psychologists entails that propositional attitudes are a kind of abstract data type. This refined computational view of propositional attitudes bridges the gap between artificial intelligence, philosophy and psychology. Lastly, it is argued that this theory of propositional attitudes has consequences for meta-processing and consciousness in computers.