Title :
SpelunkBots API - An AI toolset for Spelunky
Author :
Scales, Daniel ; Thompson, Tommy
Author_Institution :
Sch. of Comput. & Math., Univ. of Derby, Derby, UK
Abstract :
This paper describes the Spelunkbots API, a proposed benchmark for computational and articial intelligence algorithms. The benchmark, developed by the authors, is an API designed to allow for AI controllers to be written for the game Spelunky: a challenging 2D platforming game that requires players to commit quick reactive behaviours as well as long-term deliberation in order to maximise reward and minimise completion time. In this paper we highlight the features of the Spelunky game and a rationale for its relevance as an AI benchmark. Followed by a description of how the original Spelunky source code has been modified to provide a testing environment for bots. As well as some examples of simple hand-written bots, we discuss the relevance of this benchmark in the context of current AI methods.
Keywords :
application program interfaces; artificial intelligence; computer games; source code (software); 2D platforming game; AI benchmark; AI controllers; AI toolset; SpelunkBots API; Spelunky game; Spelunky source code; articial intelligence algorithm; computational algorithm; game Spelunky; reactive behaviours; testing environment;
Conference_Titel :
Computational Intelligence and Games (CIG), 2014 IEEE Conference on
Conference_Location :
Dortmund
DOI :
10.1109/CIG.2014.6932872