Intelligence without representation
Artificial Intelligence
Intelligence by design: principles of modularity and coordination for engineering complex adaptive agents
The behavior oriented design of an Unreal Tournament character
Lecture Notes in Computer Science
Programming Multi-Agent Systems in AgentSpeak using Jason (Wiley Series in Agent Technology)
Programming Multi-Agent Systems in AgentSpeak using Jason (Wiley Series in Agent Technology)
Game Development With LUA (Game Development Series)
Game Development With LUA (Game Development Series)
3D Immersion in Virtual Agents Education
ICIDS '08 Proceedings of the 1st Joint International Conference on Interactive Digital Storytelling: Interactive Storytelling
AI characters and directors for interactive computer games
IAAI'04 Proceedings of the 16th conference on Innovative applications of artifical intelligence
Agents for Games and Simulations: Trends in Techniques, Concepts and Design
Agents for Games and Simulations: Trends in Techniques, Concepts and Design
Two Case Studies for Jazzyk BSM
Agents for Games and Simulations
Unreal goal bots: conceptual design of a reusable interface
Agents for games and simulations II
An empirical study of patterns in agent programs
PRIMA'10 Proceedings of the 13th international conference on Principles and Practice of Multi-Agent Systems
IVA'11 Proceedings of the 10th international conference on Intelligent virtual agents
ICEC'12 Proceedings of the 11th international conference on Entertainment Computing
CAVE'12 Proceedings of the First international conference on Cognitive Agents for Virtual Environments
Does high-level behavior specification tool make production of virtual agent behaviors better?
CAVE'12 Proceedings of the First international conference on Cognitive Agents for Virtual Environments
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Reactive or dynamic planning is currently the dominant paradigm for controlling virtual agents in 3D videogames. Various reactive planning techniques are employed in the videogame industry while many reactive planning systems and languages are being developed in the academia. Claims about benefits of different approaches are supported by the experience of videogame programmers and the arguments of researchers, but rigorous empirical data corroborating alleged advantages of different methods are lacking. Here, we present results of a pilot study in which we compare the usability of an academic technique designed for programming intelligent agents' behavior with the usability of an unaltered classical programming language. Our study seeks to replicate the situation of professional game programmers considering using an unfamiliar academic system for programming in-game agents. We engaged 30 computer science students attending a university course on virtual agents in two programming assignments. For each, the students had to code high-level behavior of a 3D virtual agent solving a game-like task in the Unreal Tournament 2004 environment. Each student had to use Java for one task and the POSH reactive planner with a graphical editor for the other. We collected quantitative and qualitative usability data. The results indicate that POSH outperforms Java in terms of usability for one of the assigned tasks but not the other. This implies that the suitability of an AI systems-engineering approach is task sensitive. We also discuss lessons learnt about the evaluation process itself, proposing possible improvements in the experimental design. We conclude that comparative studies are a useful method for analyzing benefits of different approaches to controlling virtual agents.