Markov decision process
Related papers: 20
Top Researchers
Top Cited Papers
Point-based value iteration: an anytime algorithm for POMDPs
Joëlle Pineau, Geoff Gordon, Sebastian Thrun
Citations: 934 • 2003
Reinforcement learning for robots using neural networks
Long-Ji Lin
Citations: 887 • 1992
SARSOP: Efficient Point-Based POMDP Planning by Approximating Optimally Reachable Belief Spaces
Hanna Kurniawati, David Hsu, Wee Sun Lee
Citations: 782 • 2008
Learning to Track: Online Multi-object Tracking by Decision Making
Xiang Yu, Alexandre Alahi, Silvio Savarese
Citations: 716 • 2015
Learning policies for partially observable environments: Scaling up
Michael L. Littman, Anthony R. Cassandra, Leslie Pack Kaelbling
Citations: 662 • 1995
Acting under uncertainty: discrete Bayesian models for mobile-robot navigation
Anthony R. Cassandra, Leslie Pack Kaelbling, James Kurien
Citations: 468 • 2002
Anytime Point-Based Approximations for Large POMDPs
Joëlle Pineau, Geoff Gordon, Sebastian Thrun
Citations: 373 • 2006
Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving
Shai Shalev‐Shwartz, Shaked Shammah, Amnon Shashua
Citations: 367 • 2016
Intention-aware online POMDP planning for autonomous driving in a crowd
Haoyu Bai, Shaojun Cai, Nan Ye, David Hsu, Wee Sun Lee
Citations: 331 • 2015
Motion planning under uncertainty using iterative local optimization in belief space
Jur van den Berg, Sachin Patil, Ron Alterovitz
Citations: 305 • 2012
Autonomous helicopter control using reinforcement learning policy search methods
J. Andrew Bagnell, Jeff Schneider
Citations: 278 • 2002
Finding Approximate POMDP solutions Through Belief Compression
Nicholas Roy, Geoffrey J. Gordon, Sebastian Thrun
Citations: 253 • 2005
Deep Reinforcement Learning-Based Automatic Exploration for Navigation in Unknown Environment
Haoran Li, Qichao Zhang, Dongbin Zhao
Citations: 247 • 2019
Temporal abstraction in reinforcement learning
Doina Precup, Richard S. Sutton
Citations: 247 • 2000
Point-Based Value Iteration for Continuous POMDPs
Josep M. Porta, Nikos Vlassis, Matthijs T. J. Spaan, Pascal Poupart
Citations: 246 • 2006
Parameter-exploring policy gradients
Frank Sehnke, Christian Osendorfer, Thomas Rückstieß, Alex Graves, Jan Peters, Jürgen Schmidhuber
Citations: 245 • 2009
A Gentle Introduction to Reinforcement Learning and its Application in Different Fields
Muddasar Naeem, Syed Tahir Hussain Rizvi, Antonio Coronato
Citations: 241 • 2020
Planning under Uncertainty for Robotic Tasks with Mixed Observability
Sylvie C. W. Ong, Shao Wei Png, David Hsu, Wee Sun Lee
Citations: 238 • 2010
The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty
Ron Alterovitz, Thierry Siméon, Ken Goldberg
Citations: 236 • 2007
Planning in the Presence of Cost Functions Controlled by an Adversary
H. Brendan McMahan, Geoffrey J. Gordon, Avrim Blum
Citations: 228 • 2018