icaps 2011 - Monte-Carlo Tree Search: Theory and Applications

Monte-Carlo Tree Search: Theory and Applications

Recent advances in Monte-Carlo planning, a combination of low-overhead simulation with probabilistic decision making, have led to progress in applications ranging from networking to real-time strategy games. This workshop aims to bring together researchers interested in both theoretical analysis and applications of Monte-Carlo planning with the goal of creating a shared foundation for additional research in this area.

Call for papers

MCTS planners were developed to combat the curse of dimensionality in large state spaces and appear to have a different portfolio of strengths and weaknesses compared to traditional search methods. One example of an algorithm in this class, Upper Confidence applied to Trees (UCT), is credited with providing the foundations for new human-competitive Go-playing programs.

The success in Go motivated further work on understanding the theoretical properties of MCTS algorithms. Several papers were published questioning the tractability of these approaches in the worst case, leading to new algorithms and approaches. While trivial exponential lower bounds were proved, the success of this class of methods in real applications points towards the necessity of developing a better understanding of the type of inputs for which these algorithms perform well. Such an understanding would in turn allow a better recognition of the type of applications for which MCTS algorithms would be best suited.

The goal of this workshop is to understand the techniques that led to the breakthroughs in computer Go, translate these gains into other domains and push forward the theoretical understanding of this probabilistic planning framework. The topics include (but are not limited to):

MCTS planning in MDPs and POMDPs.
MCTS planning in games (Go, RTS games etc.).
Exploration and exploitation in MCTS algorithms.
Bandit-algorithm foundations for MCTS.
Integration of learning and planning.
Representational aspects of MCTS algorithms.
Theoretical foundations of MCTS.
Open problems.
Innovative applications of MCTS algorithms.
Work still in-progress is welcomed to the workshop under the form of position papers (which will be candidates for short, 5 minutes talks) while full-fledged research papers will be considered for long, 20 minutes talks (see submission procedure for details).

Important Dates

Submission deadline: February 11, 2011
Author notification: March 11, 2011
Camera-ready version: March 25th, 2011
Workshop date: June 12th and 13th, 2011
Submission Procedure

Papers should be submitted using EasyChair ( http://www.easychair.org/conferences/?conf=mcts11) in pdf format according to AAAI style specifications (see http://www.aaai.org/Publications/Author/author.php for details). The length of the papers should be 2 pages for position papers and 6 pages for research papers (including references).

Workshop Format

The workshop is a full day workshop and it will consist of an invited talk, a set of oral presentations (both short - 5 minutes, and long - 20 minutes), a poster session and a panel discussion.

Organizing Committee

Chris Mansley , Rutgers University, USA (contact person)
Alan Fern , Oregon State University, USA
Michael Littman , Rutgers University, USA
Sergiu Goschin , Rutgers University, USA
Program Committee

Sébastien Bubeck, Centre de Recerca Matemàtica, Spain
Malte Helmert, University of Freiburg, Germany
Martin Müller, University of Alberta, Canada
Rémi Munos, INRIA Lille, France
David Silver, University of Alberta, Canada
Csaba Szepesvári, University of Alberta, Canada
Olivier Teytaud, INRIA Saclay, France