4 citations · 8 across the 4 of their papers we have counts for
7 papers
Elastic Monte Carlo Tree Search with State Abstraction for Strategy Game Playing
Linjie Xu, Jorge Hurtado-Grueso, Dominic Jeurissen +2
Strategy video games challenge AI agents with their combinatorial search space caused by complex game elements. State abstraction is a popular technique that reduces the state spac…
Portfolio Search and Optimization for General Strategy Game-Playing
Alexander Dockhorn, Jorge Hurtado-Grueso, Dominik Jeurissen +2
Portfolio methods represent a simple but efficient type of action abstraction which has shown to improve the performance of search-based agents in a range of strategy games. We fir…
Generating Diverse and Competitive Play-Styles for Strategy Games
Diego Perez-Liebana, Cristina Guerrero-Romero, Alexander Dockhorn +3
Designing agents that are able to achieve different play-styles while maintaining a competitive level of play is a difficult task, especially for games for which the research commu…
Design and Implementation of TAG: A Tabletop Games Framework
Raluca D. Gaina, Martin Balla, Alexander Dockhorn +2
This document describes the design and implementation of the Tabletop Games framework (TAG), a Java-based benchmark for developing modern board games for AI research. TAG provides…
The Design Of "Stratega": A General Strategy Games Framework
Diego Perez-Liebana, Alexander Dockhorn, Jorge Hurtado Grueso +1
Stratega, a general strategy games framework, has been designed to foster research on computational intelligence for strategy games. In contrast to other strategy game frameworks,…
Learning Local Forward Models on Unforgiving Games
Alexander Dockhorn, Simon M. Lucas, Vanessa Volz +3
This paper examines learning approaches for forward models based on local cell transition functions. We provide a formal definition of local forward models for which we propose two…