Abstract
This paper presents an AI architecture that has been developed specifically for controlling complex multi-agents interaction in games. The model is based on previous research into Emotional Societies and presents a realistic and believable environment for games. In response to a perceived lack of depth and realism in the team relationship dynamics of modern gaming, we developed a human agent architecture, multi-agent system, and demonstrative game application. The agent architecture was based partially on research into social psychology, and utilized emotion and belief representations to drive action selection. Agent interaction and relationship development was produced on the basis of the Iterated Prisoner’s Dilemma (IPD), through which a team’s success came to be determined by its members’ choices to cooperate or compete with its leader. A produced game application illustrated the operation of the developed architecture within the context of a political street protest. A set of evaluation scenarios were devised to test the success of the project work within this game application, and ultimately found it to be successful in achieving a good level of realistic team-based reasoning and interaction. Beside the potential application of the model and architecture to a computer entertainment environment, the model is generic and can be used as well for “serious” application which involves distributed emerging behavior, scenarios based simulation, complex agent-based modeling including emotional, reactive and deliberative reasoning.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Gibson, C., O’Brien, J.: The Basics of Team AI. In: Game Developers Conference Proceedings (2001) (November 17, 2003), www.gdconf.com/archives/2001/obrien.ppt
Laird, J.E., Pottinger, D.C.: Game AI: The State of the Industry, Part Two. Gamasutra.com (November 8, 2000), http://www.gamasutra.com/features/20001108/laird_03.htm
Brehm, S.S., Kassin, S.M., Fein, S.: Social Psychology. Houghton Mifflin Company, Boston (2002)
Musse, S.R., Thalmann, D.: A Model of Human Crowd Behavior Group Inter-Relationship and Collision Detection Analysis, Citeseer (1997) (June 19, 2004), http://citeseer.ist.psu.edu/musse97model.html , http://citeseer.ist.psu.edu/bates94architecture.html
Bates, J., Loyall, A.B., Reilly, W.S.: An Architecture for Action, Emotion and Social Behavior, Citeseer. In: Brehm, S.S., Kassin, S.M., Fein, S. (eds.) Social Psychology, Houghton Mifflin Company, Boston (2002)
Silverman, B.G., et al.: Human Behavior Models for Game-Theoretic Agents: Case of Crowd Tipping. Citeseer (2002), http://citeseer.nj.nec.com/silverman02human.htm
Reynolds, J.: Tactical Team AI Using A Command Hierarchy. In: Rubin, S.H. (ed.) AI Game Programming Wisdom. Charles River Media, Inc., MA (2002)
Van Der Sterren, W.: Squad Tactics: Team AI and Emergent Maneuvers. In: Rubin, S.H. (ed.) AI Game Programming Wisdom. Charles River Media, Inc., MA (2002)
Maslow, A.H.: Motivation and Personality. Harper & Row Publishers, Inc., New York (1954)
Baker, N., El Rhalibi, A.: The Development of a Cooperative Multiagent System to Facilitate Leadership Roles in Computer Entertainment. In: ACM GDTW 2004 International Conference, November 2004, Liverpool John Moores University (2004)
Axelrod, R.: The Evolution of Cooperation. Basic Books, Inc., Publishers, NY (1957)
Reilly, W.S., Bates, J.: Building Emotional Agents, Technical Report CMU-CS-92-143, School of Computer Science, Carnegie Mellon University, Pittsburgh, USA (1992)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
El Rhalibi, A., Taleb-Bendiab, A. (2006). Harnessing Agent-Based Games Research for Analysis of Collective Agent Behavior in Critical Settings. In: Hinchey, M.G., Rago, P., Rash, J.L., Rouff, C.A., Sterritt, R., Truszkowski, W. (eds) Innovative Concepts for Autonomic and Agent-Based Systems. WRAC 2005. Lecture Notes in Computer Science(), vol 3825. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11964995_26
Download citation
DOI: https://doi.org/10.1007/11964995_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69265-2
Online ISBN: 978-3-540-69266-9
eBook Packages: Computer ScienceComputer Science (R0)