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This paper describes a doctoral research in three areas: Hybrid ASP - an extension of Answer Set Programming for reasoning about dynamical systems, an extension of Set Constraint atoms for reasoning about preferences, computing stable models of logic programs using Metropolis type algorithms. The paper discusses a possible application of all three areas to the problem of maximizing total expected reward. The main motivation for this area is the question of how to reason about dynamical systems that exhibit both discrete and continuous behavior.
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