Contribution to Book
CPN-based state analysis and prediction for multi-agent scheduling and planningin S. Fatima, T. Ito, T. Matsuo, V. Robu & M. Zhang (eds), Advances in agent-based complex automated negotiations
Document TypeBook Chapter
AbstractIn 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 patticular 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.
Citation InformationQuan Bai, Fenghui Ren, Minjie Zhang and John Fulcher. "CPN-based state analysis and prediction for multi-agent scheduling and planning" in S. Fatima, T. Ito, T. Matsuo, V. Robu & M. Zhang (eds), Advances in agent-based complex automated negotiations Vol. Springer, Berlin (2009) p. 161 - 176
Available at: http://works.bepress.com/fren/8/