The Hanabi challenge: A new frontier for AI research
- Nolan Bard
- Jakob N. Foerster
- Sarath Chandar
- Neil Burch, Department of Computing Science, University of Alberta
- Marc Lanctot
- H. Francis Song
- Emilio Parisotto
- Vincent Dumoulin
- Subhodeep Moitra
- Edward Hughes
- Iain Dunning
- Shibl Mourad
- Hugo Larochelle
- Marc G. Bellemare
- Michael Bowling, University of Alberta
From the early days of computing, games have been important testbeds for studying how well machines can do sophisticated decision making. In recent years, machine learning has made dramatic advances with artificial agents reaching superhuman performance in challenge domains like Go, Atari, and some variants of poker. As with their predecessors of chess, checkers, and backgammon, these game domains have driven research by providing sophisticated yet well-defined challenges for artificial intelligence practitioners. We continue this tradition by proposing the game of Hanabi as a new challenge domain with novel problems that arise from its combination of purely cooperative gameplay with two to five players and imperfect information. In particular, we argue that Hanabi elevates reasoning about the beliefs and intentions of other agents to the foreground. We believe developing novel techniques for such theory of mind reasoning will not only be crucial for success in Hanabi, but also in broader collaborative efforts, especially those with human partners. To facilitate future research, we introduce the open-source Hanabi Learning Environment, propose an experimental framework for the research community to evaluate algorithmic advances, and assess the performance of current state-of-the-art techniques.
Citation
N. Bard, J. Foerster, S. Chandar, N. Burch, M. Lanctot, H. Song, E. Parisotto, V. Dumoulin, S. Moitra, E. Hughes, I. Dunning, S. Mourad, H. Larochelle, M. Bellemare, M. Bowling. "The Hanabi challenge: A new frontier for AI research". Artificial Intelligence, 280, pp 103216, March 2020.| Keywords: | Multi-agent learning, Challenge paper, Reinforcement learning, Games, Theory of mind, Communication, Imperfect information, Cooperative |
| Category: | In Journal |
| Web Links: | doi |
| Elsevier |
BibTeX
@article{Bard+al:20,
author = {Nolan Bard and Jakob N. Foerster and Sarath Chandar and Neil Burch
and Marc Lanctot and H. Francis Song and Emilio Parisotto and Vincent
Dumoulin and Subhodeep Moitra and Edward Hughes and Iain Dunning and Shibl
Mourad and Hugo Larochelle and Marc G. Bellemare and Michael Bowling},
title = {The Hanabi challenge: A new frontier for AI research},
Volume = "280",
Pages = {103216},
journal = {Artificial Intelligence},
year = 2020,
}Last Updated: July 13, 2020Submitted by Sabina P
