Intelligent agent technology provides a promising basis to develop next generation tools and methods to assist decision-making. This chapter elaborates on the emergent requirements of decision support in light of recent advancements in decision science and presents a conceptual framework that serves as an agent-based architecture for decision-support. We argue that in most decision-making problems, the nature of the problem changes as the situation unfolds. Initial parameters, as well as scenarios can be irrelevant under emergent conditions. Relevant contingency decision-making models need to be identified and instantiated to continue exploration. In this paper, we suggest a multi-model framework that subsumes multiple submodels that together constitute the behavior of a complex multi-phased decisionmaking process. It has been argued that situation awareness is a critical component of experience-based decision-making style. Perception, understanding, and anticipation mechanisms are discussed as three major subsystems in realizing the situation awareness model. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Yilmaz, L., & Tolk, A. (2008). A unifying multimodel taxonomy and agent-supported multisimulation strategy for decision-support. Studies in Computational Intelligence, 97, 193–226. https://doi.org/10.1007/978-3-540-76829-6_8
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