Methods and Mechanisms for Interactive Novelty Handling in Adversarial Environments

Tung Thai, Mudit Verma, Utkarsh Soni, Sriram Gopalakrishnan, Ming Shen, Mayank Garg, Ayush Kalani, Nakul Vaidya, Neeraj Varshney, Chitta Baral, Subbarao Kambhampati, Jivko Sinapov, Matthias Scheutz

Research output: Contribution to journalConference articlepeer-review

Abstract

Learning to detect, characterize and accommodate novelties is a challenge that agents operating in open-world domains need to address to achieve satisfactory task performance. We sketch general methods for detecting and characterizing different types of novelties, and for building an appropriate adaptive model to accommodate them utilizing logical representations and reasoning methods in stochastic partially observable multi-agent environments. We also briefly report results from evaluations of our algorithms in the game domain of Monopoly. The results show high novelty detection and accommodation rates.

Original languageEnglish (US)
Pages (from-to)2385-2387
Number of pages3
JournalProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume2023-May
StatePublished - 2023
Event22nd International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2023 - London, United Kingdom
Duration: May 29 2023Jun 2 2023

Keywords

  • Adaptive Multiagent Systems
  • Agent Architecture
  • Open-world AI

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

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