[net.ai] Seminar - Probabilistic Analysis of Hierarchical Planning Problems

lohman%ibm-sj.csnet@csnet-relay.arpa (07/20/84)

From:  Guy M. Lohman <lohman%ibm-sj.csnet@csnet-relay.arpa>

           [Forwarded from the SRI bboard by Laws@SRI-AI.]

                      IBM San Jose Research Lab
                           5600 Cottle Road
                         San Jose, CA 95193


  Wed., July 25 Computer Science Seminar
  10:30 A.M.  PROBABILISTIC ANALYSIS OF HIERARCHICAL PLANNING PROBLEMS
  Aud. A      Multi-level decision problems can often be modeled as
            multi-stage stochastic programs.  Hierarchical
            planning systems designed for the solution of such
            problems can then be viewed as stochastic programming
            heuristics, and they can be subjected to the same
            kind of analytical performance analysis that has
            become customary in the area of combinatorial
            optimization.  We will give a general formulation of
            these multi-stage stochastic programs and sketch a
            framework for the design and analysis of heuristics
            for their solution.  The various ways to measure the
            performance of such heuristics are reviewed, and some
            relations between these measures are derived.  Our
            concepts are illustrated on a simple two-level
            planning problem of a general nature and on a more
            complicated two-level scheduling problem.  This talk
            is based on joint work with Alexander Rinnooy Kan and
            Leen Stougie.

            J. K. Leustra, Department of Computer Science,
            University of California at Berkeley
            Host:  B. Simons

            [...]