# Models of Continual Computation

**
Eric Horvitz**

Decision Theory & Adaptive Systems Group

Microsoft Research

Redmond, Washington 98052-6399

**Access postscript or pdf file.**

### Abstract:

Automated problem solving is viewed typically as the expenditure of
computation to solve one or more problems passed to a reasoning
system. In response to each problem received, effort is applied to
generate a solution and problem solving ends when the solution is
rendered. We discuss the notion of * continual computation * that
addresses a broader conception of * problem * by considering the
ideal use of the idle time between problem instances. The time is
used to develop solutions proactively to one or more expected
challenges in the future. We consider analyses for traditional
all-or-nothing algorithms as well as more flexible computational
procedures. After exploring the allocation of idle time for several
settings, we generalize the analysis to consider the case of shifting
computation from a current problem to solve future challenges.
Finally, we discuss a sample application of the use of continual
computation in the setting of diagnostic
reasoning.

** Keywords: ** Continual computation, bounded resources, resource-bounded reasoning, time-critical problem solving, decision-theoretic inference.

In: Proceedings of the Fourteenth National Conference on Artificial Intelligence, Providence, RI, July 1997. AAAI Press: Menlo Park.

** Author Email: **`horvitz@microsoft.com`