Research Repository

Analysis of vanilla rolling Horizon evolution parameters in general video game playing

Gaina, RD and Liu, J and Lucas, SM and Pérez-Liébana, D (2017) Analysis of vanilla rolling Horizon evolution parameters in general video game playing. In: UNSPECIFIED, ? - ?.

[img]
Preview
Text
analysis-vanilla-rolling.pdf - Accepted Version

Download (526kB) | Preview

Abstract

© Springer International Publishing AG 2017. Monte Carlo Tree Search techniques have generally dominated General Video Game Playing, but recent research has started looking at Evolutionary Algorithms and their potential at matching Tree Search level of play or even outperforming these methods. Online or Rolling Horizon Evolution is one of the options available to evolve sequences of actions for planning in General Video Game Playing, but no research has been done up to date that explores the capabilities of the vanilla version of this algorithm in multiple games. This study aims to critically analyse the different configurations regarding population size and individual length in a set of 20 games from the General Video Game AI corpus. Distinctions are made between deterministic and stochastic games, and the implications of using superior time budgets are studied. Results show that there is scope for the use of these techniques, which in some configurations outperform Monte Carlo Tree Search, and also suggest that further research in these methods could boost their performance.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Diego Perez Liebana
Date Deposited: 22 Feb 2017 15:57
Last Modified: 18 Aug 2017 10:15
URI: http://repository.essex.ac.uk/id/eprint/19038

Actions (login required)

View Item View Item