Determination of the Optimal Process Parameters in Metal

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IBM: Aglets. com/aglets/ (1998) 17, 22 4. Chen, D. : AERO: An Outsourcing Approach to Exception Handling in MultiAgent Systems. M. Math Thesis, Department of Computer Science, University of Waterloo (2001) 21 5. : Behaviors for information agents. In: Proceedings of Agents 1997 conference. (1997) 21 6. : An Exception Handling Approach to Enhancing Consistency, Completeness and Correctness in Collaborative REquirements Capture. Concurrent Engineering Research and Applications (1997) 28 7. : Domain-Independent Exception Handling Services That Increase Robustness in Open Multi-Agent Systems.

In addition, we have examined some of the ways in which AERO can be of particular assistance, given that it may be servicing multiple systems simultaneously. Since exceptions are in fact a real possibility in many agent systems, there is a need to develop methods for addressing these exceptions, in order to maintain the efficiency of these systems and to enable these systems to be better trusted by their users. The development of AERO can therefore be seen as an important part of the overall effort to design reliable agent systems.

We A Learning Algorithm for Buying and Selling Agents 39 believe that this type of learning has certain advantages: Buyers can act independently and autonomously without being affected by communication delays (due to other buyers being busy), the failure of some key-buyer (whose buying policy influences other buyers), or the reliability of the information (the information received from other buyers may not be reliable). The resultant system, therefore, should be more robust [10]. The underlying mechanism that allows agents to do business with one another in our marketplace is actually a form of the contract-net protocol [2,11], where buyers announce their desire for goods to all sellers via multicast or possibly broadcast.

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