Abstract
Adaptation in open, multi-agent information gathering systems is important for several reasons. These reasons include the inability to accurately predict future problem-solving workloads, future changes in existing information requests, future failures and additions of agents and data supply resources, and other future task environment characteristic changes that require system reorganization. We are developing a multi-agent financial portfolio management system that must deal with all of these problems. This paper will briefly describe our approaches and solutions at several different levels within the agents: adaptation at the organizational, planning, scheduling, and execution levels. We discuss our solution for execution-level adaptation (“cloning”) in detail, and present empirical evidence backing up the theory behind this execution-level solution.
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© 1997 Springer-Verlag Berlin Heidelberg
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Decker, K., Sycara, K., Williamson, M. (1997). Cloning for intelligent adaptive information agents. In: Zhang, C., Lukose, D. (eds) Multi-Agent Systems Methodologies and Applications. DAI 1996. Lecture Notes in Computer Science, vol 1286. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0030082
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DOI: https://doi.org/10.1007/BFb0030082
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