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CPN-based state analysis and prediction for multi-agent scheduling and planning

Chapter


Abstract


  • 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. © 2009 Springer-Verlag Berlin Heidelberg.

Publication Date


  • 2009

Citation


  • Bai, Q., Ren, F., Zhang, M., & Fulcher, J. (2009). CPN-based state analysis and prediction for multi-agent scheduling and planning. In Unknown Book (Vol. 233, pp. 161-176). doi:10.1007/978-3-642-03190-8_8

International Standard Book Number (isbn) 13


  • 9783642031892

Scopus Eid


  • 2-s2.0-70349989509

Web Of Science Accession Number


Book Title


  • Studies in Computational Intelligence

Start Page


  • 161

End Page


  • 176

Abstract


  • 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. © 2009 Springer-Verlag Berlin Heidelberg.

Publication Date


  • 2009

Citation


  • Bai, Q., Ren, F., Zhang, M., & Fulcher, J. (2009). CPN-based state analysis and prediction for multi-agent scheduling and planning. In Unknown Book (Vol. 233, pp. 161-176). doi:10.1007/978-3-642-03190-8_8

International Standard Book Number (isbn) 13


  • 9783642031892

Scopus Eid


  • 2-s2.0-70349989509

Web Of Science Accession Number


Book Title


  • Studies in Computational Intelligence

Start Page


  • 161

End Page


  • 176