Titlebook: Coordination of Distributed Problem Solvers; Edmund H. Durfee Book 1988 Kluwer Academic Publishers, Boston 1988 agents.artificial intellig

Keratectomy

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ainty about which goals to pursue. Some of these goals might represent alternative and conflicting solutions, and others, on further investigation, might prove to be incompatible with the problem information. By taking actions in pursuit of the goals, the problem solver can work toward acceptable so

細(xì)胞

Admire

roblem. To plan for cooperation, the nodes need to communicate about their local goals and identify the larger goals that they are cooperating to achieve. These goals are called partial global goals (PGGs): they are . in the sense that they can encompass the local goals of several nodes, but only .

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peration. Using this information, nodes alter their local actions and their interactions to work as a more effective team. This chapter focuses on how nodes develop their more coordinated plans, including techniques for negotiating over coverage of shared tasks and over transfers of tasks to use net

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Marie-Gabrielle David,Christophe Starzecd. The two principal environments are shown in Figure 68. Environment A was used for examples in the previous two chapters. Its important features are the track shared by several nodes (.-.), the much less globally-important moderately-sensed data of node 1 (.-.), and the ambiguity introduced into n

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https://doi.org/10.1007/978-1-4613-1699-2agents; artificial intelligence; autonom; communication; control; intelligence; knowledge; problem solving;