Extended Conflict-Based Search with Awareness

  • Shyni ThomasEmail author
  • Dipti Deodhare
  • M. Narasimha Murty
Part of the Studies in Computational Intelligence book series (SCI, volume 771)


Extended Conflict-Based Search (XCBS) is a distributed agent-based approach which has been used for path finding and scheduling of spatially extended agents on a traversable network. The algorithm arrives at an optimal schedule while resolving conflicts between pairs of agents one at a time. In this chapter, we propose XCBS with Awareness wherein a conflicting agent plan is resolved with respect to the proposed route plan of other agents. The approach allows multiple conflicts to be resolved simultaneously, avoids cascading conflicts in the new plans and shows an improved efficiency in terms of nodes explored and time taken to arrive at the solution.


Planning and scheduling Multi-agent Path planning Conflict resolution Search algorithm 


  1. 1.
    Standley, T., and R. Korf. 2011. Complete algorithms for cooperative pathfinding problems. In IJCAI, 668–673.Google Scholar
  2. 2.
    Qiuy Ling, Wen-Jing Hsuy, Shell-Ying Hunagy and Han Wang. 2002. Scheduling and routing algorithms for AGVs: A survey. International Journal of Production Research, 40 (3): 745–760.CrossRefGoogle Scholar
  3. 3.
    Bodin, L.D.,B.L. Golden, A. Assad, and M. Ball. 1983. Routing and scheduling of vehicles and crews: The state of the art. Computers and Operation Research, 10: 63–211.Google Scholar
  4. 4.
    Thomas, S., D. Deodhare, and M.N. Murty. 2015. Extended Conflict Based Search for Convoy Movement Problem. IEEE Intelligent Systems 60 (3): 67–76.Google Scholar
  5. 5.
    Dinh, H.T., R.S. Rinde, T. Holvoet. 2016. Multi-agent route planning using delegate MAS. In ICAPS proceedings of the 4th workshop on distributed and multi-agent planning, 24–32.Google Scholar
  6. 6.
    Kumar A., I. Murugeswari, D. Khemani and N. Narayanaswamy. Planning for convoy movement problem. In ICAART 2012-Proceedings of the 4th International Conference on Agents and Artificial Intelligence, 495–498.Google Scholar
  7. 7.
    Thomas, S., N. Dhiman, P. Tikkas, A. Sharma and D. Deodhare. 2008. Towards faster execution of OODA loop using dynamic Decision Support System. In 3rd international conference on information warfare and security (ICIW).Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Shyni Thomas
    • 2
    • 1
    Email author
  • Dipti Deodhare
    • 1
  • M. Narasimha Murty
    • 2
  1. 1.Centre for AI & Robotics (CAIR), DRDOBengaluruIndia
  2. 2.Department of Computer Science and AutomationIndian Institute of Science (IISc)BengaluruIndia

Personalised recommendations