Summary
In Agent Based Scheduling and Planning Systems, autonomous agents are used to represent enterprises and operating scheduling/planning tasks. As application domains become more and more complex, agents are required to handle a number of changing and uncertain factors. This requirement makes it necessary to embed state prediction mechanisms in Agent Based Scheduling and Planning Systems. In this chapter, we introduce a Colored Petri Net based approach that use Colored Petri Net models to represent relative dynamic factors of scheduling/planning. Furthermore, in our approach, we first introduce and adopt an improved Colored Petri Net model which can not only analyse future states of a system but also estimate the success possibility of reaching a particular future state. By using the improved Colored Petri Net model, agents can predict the possible future states of a system and risks of reaching those states. Through embedding such mechanisms, agents can make more rational and accurate decisions in complex scheduling and planning problems.
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Bai, Q., Ren, F., Zhang, M., Fulcher, J. (2009). CPN-Based State Analysis and Prediction for Multi-agent Scheduling and Planning. In: Ito, T., Zhang, M., Robu, V., Fatima, S., Matsuo, T. (eds) Advances in Agent-Based Complex Automated Negotiations. Studies in Computational Intelligence, vol 233. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03190-8_8
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DOI: https://doi.org/10.1007/978-3-642-03190-8_8
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