Studies in Computational Intelligence, 2008, Volume 97/2008, 193-226, DOI: 10.1007/978-3-540-76829-6_8

A Unifying Multimodel Taxonomy and Agent-Supported Multisimulation Strategy for Decision-Support

Levent Yilmaz and Andreas Tolk

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Abstract

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.

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