Defeasible Decisions: What the Proposal is and isn't

TL;DR

This paper explores a defeasible reasoning approach to decision analysis, positioning it as an alternative to Bayesian models, and discusses its potential to unify planning and decision theory while addressing meta-decision issues.

Contribution

It introduces a defeasible reasoning framework for decision analysis, offering a middle ground between traditional Bayesian approaches and heuristic methods, with initial ideas on argumentation heuristics.

Findings

Framework allows integration of planning and decision theory.

Stops meta-decision regress in a reasonable way.

Heuristics for argument production are promising but need further development.

Abstract

In two recent papers, I have proposed a description of decision analysis that differs from the Bayesian picture painted by Savage, Jeffrey and other classic authors. Response to this view has been either overly enthusiastic or unduly pessimistic. In this paper I try to place the idea in its proper place, which must be somewhere in between. Looking at decision analysis as defeasible reasoning produces a framework in which planning and decision theory can be integrated, but work on the details has barely begun. It also produces a framework in which the meta-decision regress can be stopped in a reasonable way, but it does not allow us to ignore meta-level decisions. The heuristics for producing arguments that I have presented are only supposed to be suggestive; but they are not open to the egregious errors about which some have worried. And though the idea is familiar to those who have studied heuristic search, it is somewhat richer because the control of dialectic is more interesting than the deepening of search.