We present a novel POMDP planning algorithm called heuristic search value iteration (HSVI). HSVI is an anytime algorithm that returns a policy and a provable bound on its regret with respect to the optimal policy. HSVI gets its power by combining two well-known tech-niques: attention-focusing search heuristics and piecewise linear convex representations of the value function. HSVI’s soundness and con-vergence have been proven. On some bench-mark problems from the literature, HSVI dis-plays speedups of greater than 100 with respect to other state-of-the-art POMDP value iteration algorithms. We also apply HSVI to a new rover exploration problem 10 times larger than most POMDP problems in the literature.
POMDP algorithms have made significant progress in recent years by allowing practitioners to find go...
The Partially Observable Markov Decision Process has long been recognized as a rich framework for re...
The search for finite-state controllers for partially observable Markov decision processes (POMDPs) ...
We present a novel POMDP planning algorithm called heuristic search value iteration (HSVI). HSVI i
Partially observable Markov decision processes (POMDPs) are the standard models for planning under u...
Trial-based asynchronous value iteration algorithms for large Partially Observable Markov Decision P...
The difficulty of POMDP planning depends on the size of the search space involved. Heuris-tics are o...
Recent algorithms like RTDP and LAO * combine the strength of Heuristic Search (HS) and Dynamic Prog...
Heuristic search-based planners, such as HSP 2.0, solve STRIPS-style planning problems efficiently ...
Planning in partially observable environments remains a challenging problem, de-spite significant re...
Partially observable Markov decision processes (POMDPs) have recently become pop-ular among many AI ...
Partially Observable Markov Decision Processes (pomdps) are gen-eral models of sequential decision p...
Abstract. Computing optimal or approximate policies for partially observable Markov decision process...
Value iteration is a popular algorithm for finding near optimal policies for POMDPs. It is inefficie...
POMDP algorithms have made significant progress in recent years by allowing practitioners to find go...
POMDP algorithms have made significant progress in recent years by allowing practitioners to find go...
The Partially Observable Markov Decision Process has long been recognized as a rich framework for re...
The search for finite-state controllers for partially observable Markov decision processes (POMDPs) ...
We present a novel POMDP planning algorithm called heuristic search value iteration (HSVI). HSVI i
Partially observable Markov decision processes (POMDPs) are the standard models for planning under u...
Trial-based asynchronous value iteration algorithms for large Partially Observable Markov Decision P...
The difficulty of POMDP planning depends on the size of the search space involved. Heuris-tics are o...
Recent algorithms like RTDP and LAO * combine the strength of Heuristic Search (HS) and Dynamic Prog...
Heuristic search-based planners, such as HSP 2.0, solve STRIPS-style planning problems efficiently ...
Planning in partially observable environments remains a challenging problem, de-spite significant re...
Partially observable Markov decision processes (POMDPs) have recently become pop-ular among many AI ...
Partially Observable Markov Decision Processes (pomdps) are gen-eral models of sequential decision p...
Abstract. Computing optimal or approximate policies for partially observable Markov decision process...
Value iteration is a popular algorithm for finding near optimal policies for POMDPs. It is inefficie...
POMDP algorithms have made significant progress in recent years by allowing practitioners to find go...
POMDP algorithms have made significant progress in recent years by allowing practitioners to find go...
The Partially Observable Markov Decision Process has long been recognized as a rich framework for re...
The search for finite-state controllers for partially observable Markov decision processes (POMDPs) ...