Epistemological Problems of Artificial Intelligence

Abstract

Artificial intelligence (AI) problem has been divided into two parts—an epistemological part and a heuristic part. This chapter further explains this division, explains some of the epistemological problems, and presents some new results and approaches. The epistemological part of AI studies what kinds of facts about the world are available to an observer with given opportunities to observe, how these facts can be represented in the memory of a computer, and what rules permit legitimate conclusions to be drawn from these facts. It leaves aside the heuristic problems of how to search spaces of possibilities and how to match patterns. Considering epistemological problems separately has the following advantages. (1) The same problems of what information is available to an observer and what conclusions can be drawn from information arise in connection with a variety of problem solving tasks. (2) A single solution of the epistemological problems can support a wide variety of heuristic approaches to a problem. (3) AI is a very difficult scientific problem, so there are great advantages in finding parts of the problem that can be separated out and separately attacked.