Autonomous Agents for The Single Track Road Problem

Ido Shapira, Amos Azaria

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

1 Scopus citations

Abstract

We present the single track road problem. In this problem two agents face each-other at opposite positions of a road that can only have one agent pass at a time. We focus on the scenario in which one agent is human, while the other is an autonomous agent. We run experiments with human subjects in a simple grid domain, which simulates the single track road problem. We show that when data is limited, building an accurate human model is very challenging, and that a reinforcement learning agent, which is based on this data, does not perform well in practice.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence, ICTAI 2021
PublisherIEEE Computer Society
Pages81-85
Number of pages5
ISBN (Electronic)9781665408981
DOIs
StatePublished - 2021
Event33rd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2021 - Virtual, Online, United States
Duration: 1 Nov 20213 Nov 2021

Publication series

NameProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
Volume2021-November
ISSN (Print)1082-3409

Conference

Conference33rd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2021
Country/TerritoryUnited States
CityVirtual, Online
Period1/11/213/11/21

Keywords

  • Autonomous vehicles
  • Human agent
  • Human modeling
  • Reinforcement Learning
  • interaction

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