Information Shaping for Enhanced Goal Recognition of Partially-Informed Agents

Sarah Keren, Haifeng Xu, Kofi Kwapong, David Parkes, Barbara Grosz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


We extend goal recognition design to account for partially informed agents. In particular, we consider a two-Agent setting in which one agent, the actor, seeks to achieve a goal but has only incomplete information about the environment. The second agent, the recognizer, has perfect information and aims to recognize the actor s goal from its behavior as quickly as possible. As a one-Time offline intervention and with the objective of facilitating the recognition task, the recognizer can selectively reveal information to the actor. The problem of selecting which information to reveal, which we call information shaping, is challenging not only because the space of information shaping options may be large, but also because more information revelation need not make it easier to recognize an agent s goal. We formally define this problem, and suggest a pruning approach for efficiently searching the search space.We demonstrate the effectiveness and efficiency of the suggested method on standard benchmarks.

Original languageEnglish
Title of host publicationAAAI 2020 - 34th AAAI Conference on Artificial Intelligence
Number of pages8
ISBN (Electronic)9781577358350
StatePublished - 2020
Externally publishedYes
Event34th AAAI Conference on Artificial Intelligence, AAAI 2020 - New York, United States
Duration: 7 Feb 202012 Feb 2020

Publication series

NameAAAI 2020 - 34th AAAI Conference on Artificial Intelligence


Conference34th AAAI Conference on Artificial Intelligence, AAAI 2020
Country/TerritoryUnited States
CityNew York

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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