Monte-Carlo planning in large POMDPs
… POMDPs than has previously been possible. We demonstrate its effectiveness in three large
POMDPs. … We also introduce two challenging new POMDPs: 10 × 10 battleship and partially …
POMDPs. … We also introduce two challenging new POMDPs: 10 × 10 battleship and partially …
[КНИГА][B] A concise introduction to decentralized POMDPs
FA Oliehoek, C Amato - 2016 - Springer
This book presents an overview of formal decision making methods for decentralized
cooperative systems. It is aimed at graduate students and researchers in the fields of artificial …
cooperative systems. It is aimed at graduate students and researchers in the fields of artificial …
Online planning algorithms for POMDPs
S Ross, J Pineau, S Paquet, B Chaib-Draa - Journal of Artificial Intelligence …, 2008 - jair.org
… However, solving a POMDP is often intractable except for small … the various existing online
POMDP methods, analyze their … methods can handle large POMDP domains efficiently. …
POMDP methods, analyze their … methods can handle large POMDP domains efficiently. …
Monte carlo pomdps
S Thrun - Advances in neural information processing …, 1999 - proceedings.neurips.cc
… solutions for discrete POMDPs. Here we are interested in POMDPs with continuous state and
… In general, such POMDPs are not solvable exactly, and little is known about special cases …
… In general, such POMDPs are not solvable exactly, and little is known about special cases …
Solving POMDPs by searching in policy space
EA Hansen - arXiv preprint arXiv:1301.7380, 2013 - arxiv.org
… Most algorithms for solving POMDPs itera tively improve a … This paper presents an approach
to solving POMDPs that … iteration in solving infinite horizon POMDPs. It provides the founda …
to solving POMDPs that … iteration in solving infinite horizon POMDPs. It provides the founda …
Decentralized pomdps
FA Oliehoek - Reinforcement learning: state-of-the-art, 2012 - Springer
… an overview of the decentralized POMDP (DecPOMDP) framework. In a Dec-POMDP, a
team of … This chapter focuses on planning for Dec-POMDPs over a finite horizon. It covers the …
team of … This chapter focuses on planning for Dec-POMDPs over a finite horizon. It covers the …
Bayes-adaptive pomdps
S Ross, B Chaib-draa, J Pineau - Advances in neural …, 2007 - proceedings.neurips.cc
… Our goal is to extend these ideas to the more general Partially Observable MDP (POMDP) …
Adaptive POMDP. This new model allows us to (1) improve knowledge of the POMDP domain …
Adaptive POMDP. This new model allows us to (1) improve knowledge of the POMDP domain …
Grasping pomdps
K Hsiao, LP Kaelbling… - Proceedings 2007 IEEE …, 2007 - ieeexplore.ieee.org
We provide a method for planning under uncertainty for robotic manipulation by partitioning
the configuration space into a set of regions that are closed under compliant motions. These …
the configuration space into a set of regions that are closed under compliant motions. These …
A primer on partially observable Markov decision processes (POMDPs)
… We discuss the need to understand POMDP solutions that will lead to further uptake of
POMDPs in ecology. Finally, we reflect on more than 10 years of research applying POMDPs and …
POMDPs in ecology. Finally, we reflect on more than 10 years of research applying POMDPs and …
Solving POMDPs by searching the space of finite policies
N Meuleau, KE Kim, LP Kaelbling… - arXiv preprint arXiv …, 2013 - arxiv.org
Solving partially observable Markov decision processes (POMDPs) is highly intractable in
general, at least in part because the optimal policy may be infinitely large. In this paper, we …
general, at least in part because the optimal policy may be infinitely large. In this paper, we …