Shimon Whiteson
Alumni
Shimon's research is primarily focused on single- and multi-agent decision-theoretic planning and learning, especially reinforcement learning, though he is also interested in stochastic optimization methods such as neuroevolution. Current research efforts include comparing disparate approaches to reinforcement learning, developing more rigorous frameworks for empirical evaluations, improving the scalability of multiagent planning, and applying learning methods to traffic management, helicopter control, and data filtering in high energy physics.
Homepage:
http://staff.science.uva.nl/~whiteson
Publications
     [Expand to show all 15][Minimize]
Protecting Against Evaluation Overfitting in Empirical Reinforcement Learning 2011
Shimon Whiteson and Brian Tanner and Matthew E. Taylor and Peter Stone
Critical Factors in the Empirical Performance of Temporal Difference and Evolutionary Methods for Reinforcement Learning 2009
Shimon Whiteson and Matthew E. Taylor and Peter Stone
Generalized Domains for Empirical Evaluations in Reinforcement Learning 2009
Shimon Whiteson and Brian Tanner and Matthew E. Taylor and Peter Stone
Adaptive Tile Coding for Value Function Approximation 2007
Shimon Whiteson and Matthew E. Taylor and Peter Stone
Empirical Studies in Action Selection for Reinforcement Learning 2007
Shimon Whiteson and Matthew E. Taylor and Peter Stone
Temporal Difference and Policy Search Methods for Reinforcement Learning: An Empirical Comparison 2007
Matthew E. Taylor and Shimon Whiteson and Peter Stone
Transfer via Inter-Task Mappings in Policy Search Reinforcement Learning 2007
Matthew E. Taylor and Shimon Whiteson and Peter Stone
Comparing Evolutionary and Temporal Difference Methods for Reinforcement Learning 2006
Matthew Taylor and Shimon Whiteson and Peter Stone
Evolutionary Function Approximation for Reinforcement Learning 2006
Shimon Whiteson and Peter Stone
On-Line Evolutionary Computation for Reinforcement Learning in Stochastic Domains 2006
Shimon Whiteson and Peter Stone
Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning 2006
Shimon Whiteson and Peter Stone
Automatic Feature Selection via Neuroevolution 2005
Shimon Whiteson and Peter Stone and Kenneth O. Stanley and Risto Miikkulainen and Nate Kohl
Evolving Keepaway Soccer Players through Task Decomposition 2005
Shimon Whiteson and Nate Kohl and Risto Miikkulainen and Peter Stone
Adaptive Job Routing and Scheduling 2004
Shimon Whiteson and Peter Stone
Concurrent Layered Learning 2003
Shimon Whiteson and Peter Stone
Projects
Cooperative Coevolution of Multi-Agent Systems 2000 - 2007
NEAT: Evolving Increasingly Complex Neural Network Topologies 2000 - 2011
Areas of Interest
Reinforcement Learning Neuroevolution Game Playing
Labs
Learning Agents