Symbolic Decision Theory and Autonomous Systems

The ability to reason under uncertainty and with incomplete information is a fundamental require­ ment of decision support technology. In this paper we argue that the concentration on theoretical techniques for the evaluation and selection of de­ cision options has distracted attention from many of the wider issues in decision making. Although numerical methods of reasoning under uncertain­ ty have strong theoretical foundations, they are representationally weak and only deal with a small part of the decision process. Knowledge­ based systems, on the other hand, offer greater flexibility but have not been accompanied by a clear decision theory. We describe here work which is under way towards providing a theoreti­ cal framework for symbolic decision procedures. A central proposal is an extended form of infer­ ence which we call argumentation; reasoning for and against decision options from generalised do­ main theories. The approach has been successful­ ly used in several decision support applications, but it is argued that a comprehensive decision the­ ory must cover autonomous decision making, where the agent can formulate questions as well as take decisions. A major theoretical challenge for this theory is to capture the idea of reflection to permit decision agents to reason about their goals, what they believe and why, and what they need to know or do in order to achieve their goals.