Online macro generation for privacy preserving planning

Shlomi Maliah, Guy Shani, Ronen Brafman

Research output: Contribution to journalConference articlepeer-review

9 Scopus citations

Abstract

Agents that use Multi-Agent Forward Search (MAFS) to do privacy-preserving planning, often repeatedly develop similar paths. We describe a simple technique for online macro generation allowing agents to reuse successful previous action sequences. By focusing on specific sequences that end with a single public action only, we are able to address the utility problem - our technique has negligible cost, yet provides both speedups and reduced communication in domains where agents have a reasonable amount of private actions. We describe two variants of our approach, both with attractive privacy preserving properties, and demonstrate the value of macros empirically. We also show that one variant is equivalent to secure MAFS.

Original languageEnglish
Pages (from-to)216-220
Number of pages5
JournalProceedings International Conference on Automated Planning and Scheduling, ICAPS
Volume2016-January
StatePublished - 1 Jan 2016
Event26th International Conference on Automated Planning and Scheduling, ICAPS 2016 - London, United Kingdom
Duration: 12 Jun 201617 Jun 2016

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management

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