Algorithms for Multi-criteria Optimization in Possibilistic Decision Trees
نویسندگان
چکیده
This paper raises the question of solving multi-criteria sequential decision problems under uncertainty. It proposes to extend to possibilistic decision trees the decision rules presented in [1] for non sequential problems. It present a series of algorithms for this new framework: Dynamic Programming can be used and provide an optimal strategy for rules that satisfy the property of monotonicity. There is no guarantee of optimality for those that do not hence the definition of dedicated algorithms. This paper concludes by an empirical comparison of the algorithms.
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