The University of Southampton
University of Southampton Institutional Repository

Automated Planning in Repeated Adversarial Games

Record type: Conference or Workshop Item (Other)

Game theory's prescriptive power typically relies on full rationality and/or self-play interactions. In contrast, this work sets aside these fundamental premises and focuses instead on heterogeneous autonomous interactions between two or more agents. Specifically, we introduce a new and concise representation for repeated adversarial (constant-sum) games that highlight the necessary features that enable an automated planing agent to reason about how to score above the game's Nash equilibrium, when facing heterogeneous adversaries. To this end, we present TeamUP, a model-based RL algorithm designed for learning and planning such an abstraction. In essence, it is somewhat similar to R-max with a cleverly engineered reward shaping that treats exploration as an adversarial optimization problem. In practice, it attempts to find an ally with which to tacitly collude (in more than two-player games) and then collaborates on a joint plan of actions that can consistently score a high utility in adversarial repeated games. We use the inaugural Lemonade Stand Game Tournament to demonstrate the effectiveness of our approach, and find that TeamUP is the best performing agent, demoting the Tournament's actual winning strategy into second place. In our experimental analysis, we show hat our strategy successfully and consistently builds collaborations with many different heterogeneous (and sometimes very sophisticated) adversaries.

PDF MCSJ10UAI.pdf - Version of Record
Download (204kB)

Citation

Munoz de Cote, Enrique, Chapman, Archie, Sykulski, Adam M. and Jennings, Nick (2010) Automated Planning in Repeated Adversarial Games At 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010), United States. 08 - 11 Jul 2010. , pp. 376-383.

More information

Published date: July 2010
Additional Information: Event Dates: 8-11 July, 2010
Venue - Dates: 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010), United States, 2010-07-08 - 2010-07-11
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 271306
URI: http://eprints.soton.ac.uk/id/eprint/271306
PURE UUID: 62ee5f38-5da2-4209-8e50-38685bce1ba7

Catalogue record

Date deposited: 25 Jun 2010 10:12
Last modified: 18 Jul 2017 06:44

Export record

Contributors

Author: Enrique Munoz de Cote
Author: Archie Chapman
Author: Adam M. Sykulski
Author: Nick Jennings

University divisions


Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×