Author:
Yevgeniy Vorobeychik
Affiliation:
Sandia National Laboratories, United States
Keyword(s):
Bidding agents, Keyword auctions, Game theory.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Bioinformatics
;
Biomedical Engineering
;
Computational Intelligence
;
Economic Agent Models
;
Enterprise Information Systems
;
Evolutionary Computing
;
Information Systems Analysis and Specification
;
Methodologies and Technologies
;
Operational Research
;
Simulation
;
Soft Computing
;
Symbolic Systems
;
Uncertainty in AI
Abstract:
TAC/AA (ad auction game) provides a forum for research into strategic bidding in keyword auctions to try out their ideas in an independently simulated setting. We describe an agent that successfully competed in the TAC/AA game, showing in the process how to operationalize game theoretic analysis to develop a very simple, yet highly competent agent. Specifically, we use simulation-based game theory to approximate equilibria in a restricted bidding strategy space, assess their robustness in a normative sense, and argue for relative plausibility of equilibria based on an analogy to a common agent design methodology. Finally, we offer some evidence for the efficacy of equilibrium predictions based on TAC/AA tournament data.