Strategy and mechanism lessons from the first ad auctions trading agent competition

Authors:
Patrick R. Jordan;Michael P. Wellman;Guha Balakrishnan
Affiliations:
Yahoo! Labs, Santa Clara, CA, USA;University of Michigan, Ann Arbor, MI, USA;University of Michigan, Ann Arbor, MI, USA
Venue:
Proceedings of the 11th ACM conference on Electronic commerce
Year:
2010

Citing 12
Cited 3

Empirical mechanism design: methods, with application to a supply-chain scenario

EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Revenue analysis of a family of ranking rules for keyword auctions

Proceedings of the 8th ACM conference on Electronic commerce
Allocating online advertisement space with unreliable estimates

Proceedings of the 8th ACM conference on Electronic commerce
AdWords and generalized online matching

Journal of the ACM (JACM)
Autonomous Bidding Agents: Strategies and Lessons from the Trading Agent Competition (Intelligent Robotics and Autonomous Agents)

Autonomous Bidding Agents: Strategies and Lessons from the Trading Agent Competition (Intelligent Robotics and Autonomous Agents)
Empirical game-theoretic analysis of the TAC Supply Chain game

Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Mechanism design and analysis using simulation-based game models

Mechanism design and analysis using simulation-based game models
Approximate strategic reasoning through hierarchical reduction of large symmetric games

AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Efficient statistical methods for evaluating trading agent performance

AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Strategy exploration in empirical games

Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
TacTex09: a champion bidding agent for ad auctions

Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Practical strategic reasoning with applications in market games

Practical strategic reasoning with applications in market games

Using iterated reasoning to predict opponent strategies

The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Using Priced Options to Solve the Exposure Problem in Sequential Auctions

ACM Transactions on Internet Technology (TOIT)
An empirical study of trading agent robustness

Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems

Quantified Score

Hi-index	0.03

Visualization

Abstract

The inaugural tournament for the Trading Agent Competition Ad Auctions game was held in July 2009. We describe the results, identifying key strategic behavior of the top agents in the competition. Through post-tournament simulation, we construct an empirical game using the agents and mechanism from the competition, and derive equilibria of this game. We then vary the auction mechanism used in simulation, and construct and solve an empirical game for each respective mechanism. Using the derived equilibria as predictions of play, we analyze revenue implications of these mechanism variations.