- author = "Alexandros Agapitos and Michael O'Neill and Anthony Brabazon and Theodoros Theodoridis",
- title = "Learning Environment Models in Car Racing Using Stateful Genetic Programming",
- booktitle = "Proceedings of the 2011 IEEE Conference on Computational Intelligence and Games",
- year = "2011",
- address = "Seoul, South Korea",
- pages = "219--226",
- month = "31 " # aug # " - 3 " # sep,
- publisher = "IEEE",
- keywords = "genetic algorithms, genetic programming, Reinforcement Learning, Multiobjective Evolution, AI in Computer Games, Car Racing, AI game agent, computational intelligence, diverse opponent generation, game play learning, nonplayer character, computer games, evolutionary computation, learning (artificial intelligence), multi-agent systems, 2D data structures, artificial agents, car racing games, learning environment models, model building behaviour, modular programs, non player characters, cognition, computer games, data structures, learning (artificial intelligence), multi-agent systems",
- isbn13 = "978-1-4577-0010-1",
-
URL = "
http://cilab.sejong.ac.kr/cig2011/proceedings/CIG2011/papers/paper54.pdf",
-
DOI = "
10.1109/CIG.2011.6032010",
- size = "8 pages",
- abstract = "For computational intelligence to be useful in creating game agent AI we need to focus on methods that allow the creation and maintenance of models for the environment, which the artificial agents inhabit. Maintaining a model allows an agent to plan its actions more effectively by combining immediate sensory information along with a memories that have been acquired while operating in that environment. To this end, we propose a way to build environment models for non-player characters in car racing games using stateful Genetic Programming. A method is presented, where general-purpose 2-dimensional data-structures are used to build a model of the racing track. Results demonstrate that model-building behaviour can be cooperatively coevolved with car-controlling behaviour in modular programs that make use of these models in order to navigate successfully around a racing track.",
-
notes = "Indexed memory.
Also known as \cite{6032010}",
