Abstract
In this paper we present a conceptualization and a formalization to define agents’ behaviors (as exhibited in agent to agent interactions), via an extension of Petri Nets, and show how behaviors of different agents can be aligned. We explain why these agents can be considered anticipatory, and the link between Business Information Systems and anticipatory systems is elaborated. We show that alignment is a state anticipatory mechanism, where predictions about future states directly influence current behavioral decision making. This results in faster and more reliable interaction execution. Also, alignment provides a mechanism for more direct behavioral learning. We investigated three manners of alignment, individual on-the-fly alignment, pre-interaction alignment, and alignment with the intervention of a third party. This paper explains in some detail how alignment on-the-fly is realized using alignment policies. The features of the other two kinds of alignment are discussed, and future directions for research are pointed out.
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Meyer, G.G., Szirbik, N.B. (2007). Anticipatory Alignment Mechanisms for Behavioral Learning in Multi Agent Systems. In: Butz, M.V., Sigaud, O., Pezzulo, G., Baldassarre, G. (eds) Anticipatory Behavior in Adaptive Learning Systems. ABiALS 2006. Lecture Notes in Computer Science(), vol 4520. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74262-3_18
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DOI: https://doi.org/10.1007/978-3-540-74262-3_18
Publisher Name: Springer, Berlin, Heidelberg
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