17 citations · 22 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
Rinascimento: Optimising Statistical Forward Planning Agents for Playing Splendor
Ivan Bravi, Simon Lucas, Diego Perez-Liebana +1
Game-based benchmarks have been playing an essential role in the development of Artificial Intelligence (AI) techniques. Providing diverse challenges is crucial to push research to…
A Local Approach to Forward Model Learning: Results on the Game of Life Game
Simon M. Lucas, Alexander Dockhorn, Vanessa Volz +6
This paper investigates the effect of learning a forward model on the performance of a statistical forward planning agent. We transform Conway's Game of Life simulation into a sing…
Efficient Evolutionary Methods for Game Agent Optimisation: Model-Based is Best
Simon M. Lucas, Jialin Liu, Ivan Bravi +4
This paper introduces a simple and fast variant of Planet Wars as a test-bed for statistical planning based Game AI agents, and for noisy hyper-parameter optimisation. Planet Wars…