Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
Recently, `determinization in hindsight' has enjoyed surprising success in on-line probabilistic planning. This technique evaluates the actions available in the current state...
In this paper we propose a suite of techniques for planning with temporally extended preferences (TEPs). To this end, we propose a method for compiling TEP planning problems into ...
Jorge A. Baier, Fahiem Bacchus, Sheila A. McIlrait...
We consider the problem of finding generalized plans for situations where the number of objects may be unknown and unbounded during planning. The input is a domain specification...
Siddharth Srivastava, Neil Immerman, Shlomo Zilber...
Abstract. Interleaved planning and scheduling employs the idea of extending partial plans by regularly heeding to the scheduling constraints during search. One of the techniques us...