A Real-Time Agent Architecture: Design, Implementation and Evaluation
The task at hand is the design and implementation of real-time agents that are situated in a changeful, unpredictable, and time-constrained environment. Based on Neisser’s human cognition model, we propose an architecture for real-time agents. This architecture consists of three components, namely perception, cognition, and action, which can be realized as a set of concurrent administrator and worker processes. These processes communicate and synchronize with one another for real-time performance. The design and implementation of our architecture are highly modular and encapsulative, enabling users to plug in different components for different agent behavior. In order to verify the feasibility of our proposal, we construct a multi-agent version of a classical real-time arcade game “Space Invader” using our architecture. In addition, we also test the competitive ratio, a measure of goodness of on-line scheduling algorithms, of our implementation against results from idealized and simplified analysis. Results confirm that our task scheduling algorithm is both efficient and of good solution quality.
KeywordsExpense Defend Dispatch Subsys
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- 1.R.P. Bonasso, D. Kortenkamp, D. Miller, and M. Slack. Experiments with an architecture for intelligent, reactiveagents. Intelligent Agents II, Lecture Notes in ArtificialIntelligence, pages 187–202, 1995.Google Scholar
- 2.R.A. Brooks. A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation, 2(1):14–23, 1986.Google Scholar
- 3.Rodney A. Brooks. Intelligence without reason. In Ray Myopoulos, John; Reiter, editor, Proceedings of the 12th International Joint Conference on Artificial Intelligence, pages 569–595, Sydney, Australia, 1991. Morgan Kaufmann.Google Scholar
- 4.B D’Ambrosio. Resource bounded-agents in an uncertain world. In Proceedings of the Workshop on Real-Time Artificial Intelligence Problems (IJCAI-89, Detroit), 1989.Google Scholar
- 6.M. Grotschel, S.O. Krumke, J. Rambau, T. Winter, and U. Zimmermann. Combinatorial online optimization in real time. In Martin Grotschel, Sven O. Krumke, and Jörg Rambau, editors, Online Optimization of Large Scale Systems—Collection of Results in the DFG-Schwerpunktprogramm Echtzeit-Optimierung groser Systeme (803 pages). Springer, 2001.Google Scholar
- 7.D. Hildebrand. An architectural overview of QNX. In Proceedings of the Usenix Worshop on Micro-Kernels & Other Kernel Architectures, Seattle, U.S.A., April 1992.Google Scholar
- 9.Jane W.S. Liu, editor. Real-Time Systems. Prentice-Hall, 2000.Google Scholar
- 10.J.P. Muller. The Design of Intelligent Agents: A Layered Approach. (LNAI Volume 1177). Springer-Verlag: Berlin, Germany, 1997.Google Scholar
- 11.H. Nakashima and I. Noda. Dynamic subsumption architecture for programming intelligent agents. In Proceedings of the International Conference on Multi-Agent Systems, pages 190–197. AAAI Press, 1998.Google Scholar
- 12.Ulric Neisser. Cognition and Reality: Principles and Implications of Cognitive Psychology. W.H. Freeman, 1976.Google Scholar
- 13.Gerhard Weiss, editor. Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence. The MIT Press, 1999.Google Scholar