Abstract
We present a novel cognitive agent architecture and demonstrate its effectiveness in the Sense and Respond Logistics (SRL) domain. SRL transforms the static, hierarchical architectures of traditional military models into re-configurable networks designed to encourage coordination among small peer units. Multi-agent systems are ideal for SRL because they can provide valuable automation and decision support from low-level control to high-level information synchronization. In particular, agents can be aware of and adapt to changes in the environment that may affect control and decision making. Our architecture, the Engine for Composable Logical Agents with Intuitive Reorganization (ECLAIR) is a framework for enabling rapid development of coherent agent systems that adapt to their environment once deployed. ECLAIR is based on cognitive theories for motivation and adaptation, including Piaget’s Assimilation and Accommodation [21] and Damasio’s Somatic Marker Hypothesis [6]. To demonstrate our preliminary work, we implemented a simple simulation environment where our agents handle the ordering and delivery of supplies among operational and supply units in several scenarios requiring adaptation of default behavior.
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References
Anderson, J.R., Bothell, D., Byrne, M.D., Douglass, S., Lebiere, C.: An integrated theory of mind. Psychological Review 111(4), 1036–1060 (2004)
Buczak, A.L., Cooper, D.G., Hofmann, M.O.: Evolutionary platform for agent learning. In: Proceedings of the Intelligent Engineering Systems Through Artificial Neural Networks, New York, vol. 14, pp. 157–164. ASME Press (2004)
Buczak, A.L., Greene, K., Cooper, D.G., Czajkowski, M., Hofmann, M.O.: A cognitive agent architecture optimized for adaptivity. In: Submission to Artificial Neural Networks in Engineering, ANNIE 2005 (2005)
Cooper, D.G.: Context based shared understanding for situation awareness. In: Proceedings of the MSS National Symposium on Sensor and Data Fusion, 2004 (2004)
Czajkowski, M., Buczak, A.L., Hofmann, M.O.: Dynamic agent composition from semantic web services. In: Bussler, C.J., Tannen, V., Fundulaki, I. (eds.) SWDB 2004. LNCS, vol. 3372, pp. 27–40. Springer, Heidelberg (2005)
Damasio, A.R.: Descartes’ Error: Emotion, Reason, and the Human Brain. G.P. Putnam, New York (1994)
Decker, K.S., Sycara, K.: Intelligent adaptive information agents. In: Imam, I. (ed.) Working Notes of the AAAI 1996 Workshop on Intelligent Adaptive Agents, Portland, OR (1996)
Defense and the National Interest. Fourth Generation Warfare, http://www.d-n-i.net/second_level/fourth_generation_warefare.htm
Franke, J., Satterfield, B., Jameson, S.: Information sharing in teams of selfaware entities. In: Proceedings of the The Second International Workshop on Multi-Robot Systems NRL (2003)
Gerken, P., Jameson, S., Sidharta, B., Barton, J.: Improving army aviation situational awareness with agent-based data discovery. In: Proceedings of the American Helicopter Society Conference (2003)
Haynes, T., Wainwright, R., Sen, S.: Evolving cooperation strategies. In: Lesser, V. (ed.) Proceedings of the First International Conference on Multi–Agent Systems, San Francisco, CA. MIT Press, Cambridge (1995)
Helsinger, A., Thome, M., Wright, T.: Cougaar: a scalable, distributed multiagent architecture. In: Systems, Man and Cybernetics, vol. 2, pp. 1910–1917. IEEE, Los Alamitos (2004)
Ioerger, T.R., Volz, R.A., Yen, J.: Modeling cooperative, reactive behaviors on the battlefield using intelligent agents. In: Proceedings of the The Ninth Conference on Computer Generated Forces (9th CGF), pp. 13–23 (2000)
Jones, R.M., Laird, J.E., Nielsen, P.E., Coulter, K.J., Kenny, P., Koss, F.V.: Automated intelligent pilots for combat flight simulation. AI Magazine 20(1), 27–41 (1999)
Kaelbling, L.P., Littman, M.L., Moore, A.W.: Reinforcement learning: A survey. Journal of Artificial Intelligence Research 4, 237–285 (1996)
Koza, J.R.: Genetic Programming: On the Programming of Computers by Natural Selection. MIT Press, Cambridge (1992)
Lewis, R.L.: Coginitive theory, soar. Tech. rep., Ohio State University, Department of Computer Science (1999)
Littman, M.L.: Markov games as a framework for multi-agent reinforcement learning. In: Proceedings of the 11th International Conference on Machine Learning (ML 1994), New Brunswick, NJ, pp. 157–163. Morgan Kaufmann, San Francisco (1994)
Lockheed Martin Advanced Technology Laboratories. Cooperative Agents for Specific Tasks (CAST), http://www.atl.lmco.com/overview/programs/IS/CAST.html
Lockheed Martin Advanced Technology Laboratories, http://www.atl.lmco.com/overview/library.html
Miller, P.H.: Theories of Development Psychology. W.H. Freeman and Co., New York (1983)
Nason, S., Laird, J.E.: Soar-rl: Integrating reinforcement learning with soar. Tech. rep., University of Michigan (2004)
Newell, A.: Unified Theories of Cognition. Harvard University Press, Cambridge (1990)
Office of Force Transformation, United States Department of Defense. Operational Sense and Respond Logistics: Coevolution of an Adaptive Enterprise Capability (2004); Concept document in progress
Simon, S.J.: The art of military logistics. Communications of the ACM 44(6), 62–66 (2001)
Sutton, R.S.: Reinforcement learning: Past, present and future. In: McKay, B., Yao, X., Newton, C.S., Kim, J.-H., Furuhashi, T. (eds.) SEAL 1998. LNCS (LNAI), vol. 1585, pp. 195–197. Springer, Heidelberg (1999)
Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (1998)
Wood, R.J.: Information engineering; the foundation of information warfare. Tech. rep., Air War College, Air University (1995)
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Greene, K., Cooper, D.G., Buczak, A.L., Czajkowski, M., Vagle, J.L., Hofmann, M.O. (2006). Cognitive Agents for Sense and Respond Logistics. In: Thompson, S.G., Ghanea-Hercock, R. (eds) Defence Applications of Multi-Agent Systems. DAMAS 2005. Lecture Notes in Computer Science(), vol 3890. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11683704_9
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DOI: https://doi.org/10.1007/11683704_9
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