Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/31036

TitleArtificial intelligence approaches for the generation and assessment of believable human-like behaviour in virtual characters
Author(s)Asensio, Joan Marc Llargues
Donate, Juan Peralta
Arrabales, R.
Bedia, M. Gonzalez
Cortez, Paulo
Penã, A. Lopez
KeywordsTuring Test
Human-Like Behaviour
Believability
Non-Player Characters
Cognitive Architectures
Genetic algorithm
Artificial Neural Networks
Issue dateNov-2014
PublisherElsevier
JournalExpert Systems With Applications
CitationIn Expert Systems With Applications, Elsevier, 41(16):7281-7290, November, 2014, ISSN 0957-4174.
Abstract(s)Having artificial agents to autonomously produce human-like behaviour is one of the most ambitious original goals of Artificial Intelligence (AI) and remains an open problem nowadays. The imitation game originally proposed by Turing constitute a very effective method to prove the indistinguishability of an artificial agent. The behaviour of an agent is said to be indistinguishable from that of a human when observers (the so-called judges in the Turing test) can not tell apart humans and non-human agents. Different environments, testing protocols, scopes and problem domains can be established to develop limited versions or variants of the original Turing test. In this paper we use a specific version of the Turing test, based on the international BotPrize competition, built in a First-Person Shooter video game, where both human players and non-player characters interact in complex virtual environments. Based on our past experience both in the BotPrize competition and other robotics and computer game AI applications we have developed three new more advanced controllers for believable agents: two based on a combination of the CERA-CRANIUM and SOAR cognitive architectures and other based on ADANN, a system for the automatic evolution and adaptation of artificial neural networks. These two new agents have been put to the test jointly with CCBot3, the winner of BotPrize 2010 competition [1], and have showed a significant improvement in the humanness ratio. Additionally, we have confronted all these bots to both First-person believability assessment (BotPrize original judging protocol) and Third-person believability assess- ment, demonstrating that the active involvement of the judge has a great impact in the recognition of human-like behaviour.
TypeArticle
URIhttp://hdl.handle.net/1822/31036
DOI10.1016/j.eswa.2014.05.004
ISSN0941-0643
Publisher versionThe original publication is available: http://dx.doi.org/10.1016/j.eswa.2014.05.004
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em revistas internacionais/Papers in international journals

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