Volume 13 Number 3 (Mar. 2018)
Home > Archive > 2018 > Volume 13 Number 3 (Mar. 2018) >
JCP 2018 Vol.13(3): 351-359 ISSN: 1796-203X
doi: 10.17706/jcp.13.3.351-359

HIPR: An Architecture for Iterative Plan Repair in Hierarchical Multi-agent Systems

Swarup Kumar Mohalik1, Mahesh Babu Jayaraman1, Ramamurthy Badrinath1, Aneta Vulgarakis Feljan2
1Ericsson Research, Bangalore-560037, India.
2Ericsson Research, Kista-16480, Sweden.

Abstract—In large scale multi-agent systems, both planning for system goals and replanning during plan execution to handle failures are compute-intensive. Since replanning requires faster response time because it happens during plan execution, a lot of focus in the AI planning literature has been on incremental methods, such as plan repair, plan modification etc., which avoid re-synthesizing a complete plan. In this paper, we propose HIPR - an architecture and supporting algorithms for fast replanning in multi-agent systems with two fairly general characteristics: (1) where the agents are organized hierarchically based on attributes like location/administration and (2) where most failures are localized i.e. only a few agents are affected by the failure while most of the agents at large remain unaffected. HIPR exploits these characteristics to identify the smallest group of agents that are affected by the failure and to synthesize new plan fragments for only these agents. The localization to smaller number of agents generates smaller replanning problems and hence more efficient solutions. We illustrate application of HIPR on a small, yet realistic route planning use case.

Index Terms—Artificial intelligence, hierarchical domains, planning, replanning.

[PDF]

Cite: Swarup Kumar Mohalik, Mahesh Babu Jayaraman, Ramamurthy Badrinath, Aneta Vulgarakis Feljan, "HIPR: An Architecture for Iterative Plan Repair in Hierarchical Multi-agent Systems," Journal of Computers vol. 13, no. 3, pp. 351-359, 2018.

General Information

ISSN: 1796-203X
Frequency: Monthly (2006-2014); Bimonthly (Since 2015)
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO, DOAJ, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
  • Sep 26, 2017 News!

    Papers published in JCP Volume 12 have all been indexed by DBLP   [Click]

  • Sep 02, 2016 News!

    Vol 11, No 3 has been indexed by EI (Inspec)   [Click]

  • Sep 22, 2017 News!

    Vol 13, No 6 has been published with online version 11 papers are published in this issue after peer review   [Click]

  • Aug 14, 2017 News!

    Vol 13, No 5 has been published with online version   [Click]

  • Jun 21, 2017 News!

    Vol 13, No 4 has been published with online version   [Click]

  • Read more>>