Automated Derivation of Primitives for Movement Classification
Autonomous Robots
Human-Level AI's Killer Application: Interactive Computer Games
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Turing's test and believable AI in games
Computers in Entertainment (CIE) - Theoretical and Practical Computer Applications in Entertainment
Virtual Institutions: Normative Environments Facilitating Imitation Learning in Virtual Agents
IVA '08 Proceedings of the 8th international conference on Intelligent Virtual Agents
Evolving interesting maps for a first person shooter
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part I
Improving game bot behaviours through timed emotional intelligence
Knowledge-Based Systems
ACSC '11 Proceedings of the Thirty-Fourth Australasian Computer Science Conference - Volume 113
Real-time human-robot interactive coaching system with full-body control interface
Robot Soccer World Cup XV
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In imitation learning, agents are trained to carry out certain actions by examining a demonstration of the task at hand Though common in robotics, little work has been done in translating these concepts to computer games Given that present-day games generally use antiquated AI techniques which can often lead to stilted, mechanical and conspicuously artificial behaviour, it seems likely that approaches based on the imitation of human players may produce agents which convey a more humanlike impression than their traditional counterparts At the same time, there exists no formal method of quantifying what constitutes a ‘humanlike' impression; an equivalent of the Turing test is needed, with the requirement that an agent's appearance and behaviour be capable of deceiving an observer into misidentifying it as human The aims of this paper are thus threefold; we describe an approach to the imitation of strategic behaviour and motion, propose a formal method of quantifying the degree to which different agents are perceived as ‘humanlike', and present the results of a series of experiments using these two systems.