Paper Info
Title
Evolving behaviour trees for the Mario AI competition using grammatical evolution
Abstract
This paper investigates the applicability of Genetic Programming type systems to dynamic game environments. Grammatical Evolution was used to evolved Behaviour Trees, in order to create controllers for the Mario AI Benchmark. The results obtained reinforce the applicability of evolutionary programming systems to the development of artificial intelligence in games, and in dynamic systems in general, illustrating their viability as an alternative to more standard AI techniques.
Year
DOI
Venue
2011
10.1007/978-3-642-20525-5_13
EvoApplications (1)
Keywords
Field
DocType
evolutionary programming system,artificial intelligence,behaviour tree,mario ai competition,behaviour trees,grammatical evolution,dynamic game environment,genetic programming type system,standard ai technique,mario ai benchmark,dynamic system,artificial intelligent,evolutionary programming,dynamic game,type system
Computer science,Genetic programming,Artificial intelligence,Game Developer,Sequential game,Behavior Trees,Grammatical evolution,Evolutionary programming
Conference
Volume
ISSN
Citations 
6624
0302-9743
24
PageRank 
References 
Authors
1.37
7
4
Name
Order
Citations
PageRank
Diego Perez138220.98
Miguel Nicolau212513.86
Michael O'Neill387669.58
Anthony Brabazon491898.60