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The apphcatlon of artlficlal neural networks for the modelhng of a complex process was examined A real data set concernmg the batch produchon of cheese from an actual plant was used to predict the resultmg water content of the cheese from the mdk cornposItIon and process parameters Owmg to the complex nature of the data and the hnuted number of available(More)
A simple framework is developed for representing plans, goals and resources of agents in order to model cooperative planning behavior. Plans are represented as acyclic networks of skills that, given adequate initial resources, can realize special resources (goals). Given the storage costs of resources, application costs of skills, and values of goals we can(More)
An important aspect of agents is how they construct a plan to reach their goals. Since most agents live in a dynamic environment, they also will often be confronted with situations in which the plans they constructed to reach their goals are no longer feasible. In such situations, agents have to change their plan to deal with the new environment. In this(More)
We introduce an algorithm for cooperative planning in multi-agent systems. The algorithm enables the agents to combine (fuse) their plans in order to increase their joint profits. A computational resources and skills framework is developed for representing the planned activities of an agent under time constraints. Using this resource-skill framework, we(More)