most citedLearning Policies from Self-Play with Policy Gradients and MCTS Value Estimates

5 citations · 8 across the 3 of their papers we have counts for

collaborators

6 papers

cs.AI2019

Ludii as a Competition Platform

Matthew Stephenson, Éric Piette, Dennis J. N. J. Soemers +1

Ludii is a general game system being developed as part of the ERC-funded Digital Ludeme Project (DLP). While its primary aim is to model, play, and analyse the full range of tradit…

cs.AI2019

Ludii and XCSP: Playing and Solving Logic Puzzles

Cédric Piette, Éric Piette, Matthew Stephenson +2

Many of the famous single-player games, commonly called puzzles, can be shown to be NP-Complete. Indeed, this class of complexity contains hundreds of puzzles, since people particu…

cs.AI2019

An Empirical Evaluation of Two General Game Systems: Ludii and RBG

Éric Piette, Matthew Stephenson, Dennis J. N. J. Soemers +1

Although General Game Playing (GGP) systems can facilitate useful research in Artificial Intelligence (AI) for game-playing, they are often computationally inefficient and somewhat…

cs.AI2019

An Overview of the Ludii General Game System

Matthew Stephenson, Éric Piette, Dennis J. N. J. Soemers +1

The Digital Ludeme Project (DLP) aims to reconstruct and analyse over 1000 traditional strategy games using modern techniques. One of the key aspects of this project is the develop…

cs.AI20193 cited

Foundations of Digital Archæoludology

Cameron Browne, Dennis J. N. J. Soemers, Éric Piette +15

Digital Archaeoludology (DAL) is a new field of study involving the analysis and reconstruction of ancient games from incomplete descriptions and archaeological evidence using mode…

cs.LG20195 cited

Learning Policies from Self-Play with Policy Gradients and MCTS Value Estimates

Dennis J. N. J. Soemers, Éric Piette, Matthew Stephenson +1

In recent years, state-of-the-art game-playing agents often involve policies that are trained in self-playing processes where Monte Carlo tree search (MCTS) algorithms and trained…