Plan recognition in exploratory domains

Reuth Mirsky, Ya'akov Gal

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

Abstract

My thesis focuses on recognition and interventions of users' activities using open-ended and flexible software. In such exploratory settings, users' behavior is characterized by exploration, mistakes and trial-and-error. Exploratory domains provide a flexible and rich interaction environment for their users, but induce challenges for automatic recognition and support of their activities. My thesis focuses on the following three challenges which are central to understanding users' interactions in exploratory settings and to use this understanding in order to provide them with effective support and guidance: (1) Representing and inferring users' interactions in exploratory domains. (2) Disambiguating between possible explanations in order to improve understanding of users' behavior. (3) Producing machine-generated support that adapts to the needs of the users. My research activities combines computational models, algorithms and empirical methodologies to meet the challenges above. They are conducted in the context of various types of exploratory settings. Specifically, I am developing novel plan recognition algorithms for inferring users' interactions in exploratory settings and intervention mechanisms for these environments. I am evaluating my approach in the real world using educational software, medical records and cyber security domains. My results so far include (1) design of a new model for plan recognition; (2) an online plan recognition algorithm that is empirically shown to outperform the state-of-the-art methods in the real world; (3) A sequential process that allows informed disambiguation of possible hypotheses describing an agent's plans. The long term impact of my contribution to computer science will be demonstrated by (1) developing new algorithms for plan recognition, intervention design and adaptation for exploratory settings; (2) showing that these methods generalize to different types of settings that differ widely in they type of interaction that is provided by the users.

Original languageEnglish
Title of host publicationAAMAS 2016 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1524-1525
Number of pages2
ISBN (Electronic)9781450342391
StatePublished - 2016
Externally publishedYes
Event15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016 - Singapore, Singapore
Duration: 9 May 201613 May 2016

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016
Country/TerritorySingapore
CitySingapore
Period9/05/1613/05/16

Bibliographical note

Publisher Copyright:
Copyright © 2016, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.

Keywords

  • Activity and plan recognition
  • Exploratory settings
  • Human-aware AI
  • Modelbased reasoning

Fingerprint

Dive into the research topics of 'Plan recognition in exploratory domains'. Together they form a unique fingerprint.

Cite this