CFP
MCS 2020: Monte Carlo Search Workshop at IJCAI 2020 IJCAI TBD, Japan, January 4-10, 2021 |
Conference website | https://www.lamsade.dauphine.fr/~cazenave/mcs2020/mcs2020.html |
Submission link | https://easychair.org/conferences/?conf=mcs2020 |
Monte Carlo Tree Search, and then Zero learning vastly improved Monte Carlo search in a wide range of applications; classic Monte Carlo search still dominates many partially observable problems. Submissions are welcome in all fields related to Monte Carlo Search, including:
- Monte Carlo Tree Search and Upper Confidence Trees;
- Nested Monte Carlo;
- Non-locality in Monte Carlo search;
- Combination with Zero learning;
- Monte Carlo Belief-state estimation;
- Self-Adaptive Monte Carlo Search;
- Monte Carlo in many player games.
- Applications:
- Industrial applications;
- Scientific applications;
- Applications in games;
- Applications in puzzles;
Submission Guidelines
Papers are written in English using LNCS style.
Committees
Organizing committee
- Tristan Cazenave, Universite Paris-Dauphine, PSL
- Olivier Teytaud, Facebook FAIR
- Mark Winands, Maastricht University
Contact
All questions about submissions should be emailed to Tristan.Cazenave@dauphine.psl.eu