### Citation

(PDF)
Peter van Beek.
An investigation of probabilistic interpretations of heuristics
in plan recognition.
*Proceedings of the Fifth International Conference on
User Modeling,*
Kailua-Kona, Hawaii, 113-120, January, 1996.

### Abstract

Plan recognition is the process of inferring a plausible set of
plans that explain an agent's actions. In this paper, I use a
small example to focus on some non-probabilistic heuristics
proposed in the literature for preferring one plan over another.
I show some of the conditions or constraints on the probability
distributions so that the plan that is preferred by the
heuristics is also the most probable plan and I look at some of
the implications of these conditions. I also show that if the
conditions do not hold there exist cases where the results of the
heuristics clash with that of probabilities. One of the most
interesting results of the analysis is that, given the assumption
that the plan library is complete, the heuristics examined can be
given a probabilistic interpretation or justification if and only
if any two basic plans in the plan library which share a step are
equally likely. The usefulness of the analysis is that we can
test whether the conditions hold in a particular domain and so
gain more insight into whether our choice of heuristic is
appropriate to that domain. Further, this work can be seen as
providing an alternative justification of the heuristics.

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