Knowledge Management & Knowledge-based Systems, Knowledge Discovery and Data Mining, Logic and Logic Programming, Machine Learning, Evolutionary Algorithms & Neural Networks, Natural Language and Speech Processing, AI Applications.

This paper describes the design of a socio-technical research system for the purpose of rescheduling train drivers in the event of disruptions. The research system is structured according to the Actor-Agentparadigm: Here agents assist in rescheduling tasks of train drivers. Coordination between agents is basedon a team formation process in which possible rescheduling alternatives can be evaluated, based onconstraints and preferences of involved human train drivers and dispatchers. The research aim is to explore the effectiveness of a decentralized, flexible actor-agent based approach to crew rescheduling. Theresearch system is realized using the Cougaar framework and includes actual rolling stock schedule dataand driver duty data. The current reduced-scale version shows promising results for the full-scale versionend 2008. 1 Netherlands Railways: Planning and Rescheduling Applied research on advanced autonomous systems in a real-world domain provides a stimulatingenvironment to demonstrate ‘state of the art’ research results and address the encountered pragmatic andfundamental challenges. The cooperation between Netherlands Railways (NS) and the D-CIS Labaddresses a complex situation: how to reschedule tasks of train drivers in response to disruptions in theirschedules. The aim is to arrive at a research system for ongoing experimentation by NS. This paperprovides a brief overview of the problem domain, the design of the actor-agent based solution, and the current midway implementation with a brief comparison with related literature.