Localized Search

Abstract

In this report, we describe the search algorithm of the GEMPLAN multiagent planning system. The search algorithm is based upon the GEMPLAN domain description and its localized constraint representation. The problem domain is structured into regions of activity, and each region has its own set of local constraints. The search is a constraint-satisfaction process; it tries to find a plan in each region by satisfying the region’s constraints. Therefore, the search space is subdivided into regional search trees. Unfortunately, these search trees cannot be searched independently. However, the situation is much better than global search because GEMPLAN’s constraint localization, together with the domain structure, precisely define when the search in one region can affect another region, and hence how control must shift from one search tree to another. To avoid any confusion, this report does not describe GEMPLAN, but only its generic localized search algorithm. We only explain and abstract features of GEMPLAN on which this search algorithm is based. As a result, this algorithm is applicable to any other constraint-satisfaction problem with characteristics similar to GEMPLAN.


Read more from SRI

  • Collage of Douglas Engelbart at the Mother of All Demos and a modern computer mouse

    Stanford celebrates a world-changing SRI invention

    Spotlighting Douglas Engelbart’s invention of the computer mouse, Stanford Magazine revisits a moment when SRI transformed computing forever.

  • Two IT professionals solving a problem

    Why quantum assurance matters

    New SRI research seeks to secure the future of quantum innovation by extending software assurance capabilities from classical computers to quantum information systems.

  • PARC Forum Participants

    PARC Forum: The future of defense technologies

    Silicon Valley is paying close attention to the defense sector. SRI convened a conversation exploring new opportunities to advance security through innovation.