Searching for an Alternative Plan

Ariel Felner, Alex Pomeransky, Jeffrey S. Rosenschein

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

Suppose that an intelligent agent accepts as input a complete plan, i.e., a sequence of states (or operators) that should be followed in order to achieve a goal. For some reason, the given plan cannot be followed by the agent, and thus an alternative plan needs to be found - but we would like the alternative plan to be as close as possible to the original. To achieve this, we define a number of distance metrics between paths or plans, and characterize these functions and their respective attributes and advantages. We then develop a general algorithm based on best-first search that helps an agent find the most suitable alternative plan efficiently, and propose a number of heuristics for the cost function of this best-first search algorithm. We then experimentally show that our algorithm is efficient in finding an alternative plan.

Original languageEnglish
Pages33-40
Number of pages8
DOIs
StatePublished - 1 Jan 2003
Externally publishedYes
EventProceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 03 - Melbourne, Vic., Australia
Duration: 14 Jul 200318 Jul 2003

Conference

ConferenceProceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 03
Country/TerritoryAustralia
CityMelbourne, Vic.
Period14/07/0318/07/03

Keywords

  • A*
  • Agents
  • Alternative Plan
  • Search

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