Decision-Theoretic Control of Problem Solving: Principles and
  Architecture
  This paper presents an approach to the design of autonomous, real-time
systems operating in uncertain environments. We address issues of problem
solving and reflective control of reasoning under uncertainty in terms of two
fundamental elements: l) a set of decision-theoretic models for selecting among
alternative problem-solving methods and 2) a general computational architecture
for resource-bounded problem solving. The decisiontheoretic models provide a
set of principles for choosing among alternative problem-solving methods based
on their relative costs and benefits, where benefits are characterized in terms
of the value of information provided by the output of a reasoning activity. The
output may be an estimate of some uncertain quantity or a recommendation for
action. The computational architecture, called Schemer-ll, provides for
interleaving of and communication among various problem-solving subsystems.
These subsystems provide alternative approaches to information gathering,
belief refinement, solution construction, and solution execution. In
particular, the architecture provides a mechanism for interrupting the
subsystems in response to critical events. We provide a decision theoretic
account for scheduling problem-solving elements and for critical-event-driven
interruption of activities in an architecture such as Schemer-II.
