We present a new algorithm for conformant probabilistic planning, which for a given horizon produces a plan that maximizes the probability of success under quantified uncertainty ...
The utility of including loops in plans has been long recognized by the planning community. Loops in a plan help increase both its applicability and the compactness of representat...
Siddharth Srivastava, Neil Immerman, Shlomo Zilber...
Symbolic universal planning based on the reduced Ordered Binary Decision Diagram (OBDD) has been shown to be an efficient approach for planning in non-deterministic domains. To d...
Rune M. Jensen, Manuela M. Veloso, Randal E. Bryan...
Memory-bounded techniques have shown great promise in solving complex multi-agent planning problems modeled as DEC-POMDPs. Much of the performance gains can be attributed to pruni...
Temporally extended goals (TEGs) refer to properties that must hold over intermediate and/or final states of a plan. Current planners for TEGs prune the search space during planni...