Solving Decision Problems by Distributed Decomposition and Delegation
This paper is based on the paradigm that the solution of a yet unstructured decision problem with discrete action alternatives requires planning of the problem solution process (the invention of a new solution) prior to the execution of this plan. First, we concentrate on the design of a distributed planning process using several agents (first phase of a decision process). Following a “modeling cost approach”, the foundations of a general theory of problem decomposition and delegation of sub-problems will be developed.
Based on this description of the decompositions and delegations using the domain independent and extendible language ANDORI, we derive rules to identify the particular region of a decomposition tree promising the best compromise between modeling cost and solution quality. That means that we provide means to select the optimal node to be decomposed next. Furthermore, models of task distribution to agents are evaluated. Finally, we describe a preliminary prototype of a group decision support system based on this theory as well as the organizational environment necessary for its application.
KeywordsDecision Problem Leaf Node Search Tree Modeling Cost Search Cost
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