Accession Number:

ADA622479

Title:

Continuous Explanation Generation in a Multi-Agent Domain

Descriptive Note:

Journal article preprint

Corporate Author:

NAVAL RESEARCH LAB WASHINGTON DC

Personal Author(s):

Report Date:

2015-01-01

Pagination or Media Count:

19.0

Abstract:

An agent operating in a dynamic, multi-agent environment with partial observability should continuously generate and maintain an explanation of its observations that describes what is occurring around it. We update our existing formal model of occurrence-based explanations to describe ambiguous explanations and the actions of other agents. We also introduce a new version of DiscoverHistory, an algorithm that continuously maintains such explanations as new observations are received. In our empirical study this version of DiscoverHistory outperformed a competitor in terms of efficiency while maintaining correctness i.e., precision and recall.

Subject Categories:

  • Statistics and Probability
  • Human Factors Engineering and Man Machine Systems

Distribution Statement:

APPROVED FOR PUBLIC RELEASE