On the Complexity of Decision Making in Possibilistic Decision Trees

Details On the Complexity of Decision Making in Possibilistic Decision Trees On the Complexity of Decision Making in Possibilistic Decision Trees

2012-02-14

arxiv.org/abs/1202.3718v1

Computer Science

Artificial Intelligence

Scientific paper

When the information about uncertainty cannot be quantified in a simple, probabilistic way, the topic of possibilistic decision theory is often a natural one to consider. The development of possibilistic decision theory has lead to a series of possibilistic criteria, e.g pessimistic possibilistic qualitative utility, possibilistic likely dominance, binary possibilistic utility and possibilistic Choquet integrals. This paper focuses on sequential decision making in possibilistic decision trees. It proposes a complexity study of the problem of finding an optimal strategy depending on the monotonicity property of the optimization criteria which allows the application of dynamic programming that offers a polytime reduction of the decision problem. It also shows that possibilistic Choquet integrals do not satisfy this property, and that in this case the optimization problem is NP - hard.

Affiliated with

Also associated with

No associations

Rating

On the Complexity of Decision Making in Possibilistic Decision Trees does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with On the Complexity of Decision Making in Possibilistic Decision Trees, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and On the Complexity of Decision Making in Possibilistic Decision Trees will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-90421