Monte Carlo Search 2020, IJCAI Workshop, Yokohama, Japan, 12 July 2020

In conjunction with IJCAI 2020


Monte Carlo Search is a family of general search algorithms that have many applications in different domains.

It is the state of the art in perfect and imperfect information games.

Other applications include the RNA inverse folding problem, Logistics, Multiple Sequence Alignment, General Game Playing, Puzzles, 3D Packing with Object Orientation, Cooperative Pathfinding, Software testing and heuristic Model-Checking.

In recent years, many researchers have explored different variants of the algorithms, their relations to Deep Reinforcement Learning and their different applications.

The purpose of this workshop is to bring these researchers together to present their research, discuss future research directions, and cross-fertilize the different communities.

Researchers and practitioners whose research might benefit from Monte Carlo Search in their research are welcome.

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:


Papers are written in English using LNCS style.


Submission Deadline: April 26, 2020

Acceptance Notification: May 26, 2020

Final Papers: June 26, 2020

MCS 2020: July 12, 2020


You can submit your papers using this link to Easychair


Tristan Cazenave, Universite Paris-Dauphine, PSL

Olivier Teytaud, Facebook FAIR

Mark Winands, Maastricht University