Title
Evolutionary Behavior Tree Approaches For Navigating Platform Games
Abstract
Computer games are highly dynamic environments, where players are faced with a multitude of potentially unseen scenarios. In this paper, AI controllers are applied to the Mario AI benchmark platform, by using the grammatical evolution system to evolve behavior tree structures. These controllers are either evolved to both deal with navigation and reactiveness to elements of the game or used in conjunction with a dynamic A* approach. The results obtained highlight the applicability of behavior trees as representations for evolutionary computation and their flexibility for incorporation of diverse algorithms to deal with specific aspects of bot control in game environments.
Year
DOI
Venue
2017
10.1109/TCIAIG.2016.2543661
IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES
Keywords
Field
DocType
Autonomous agents, behavior trees (BTs), benchmarking, grammatical evolution (GE), platform games, videogames
Multitude,Computer science,Evolutionary computation,Artificial intelligence,Behavior Trees,Grammatical evolution,Machine learning,Benchmark (computing)
Journal
Volume
Issue
ISSN
9
3
1943-068X
Citations 
PageRank 
References 
4
0.45
22
Authors
4
Name
Order
Citations
PageRank
Miguel Nicolau16710.26
diego perez220226.00
michael o neill359960.93
Anthony Brabazon491898.60