TY - GEN
T1 - A game theoretic bidding agent for the ad auction game
AU - Vorobeychik, Yevgeniy
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
KW - Bidding agents
KW - Game theory
KW - Keyword auctions
UR - https://www.scopus.com/pages/publications/79960135201
M3 - Conference contribution
AN - SCOPUS:79960135201
SN - 9789898425416
T3 - ICAART 2011 - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence
SP - 35
EP - 44
BT - ICAART 2011 - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence
T2 - 3rd International Conference on Agents and Artificial Intelligence, ICAART 2011
Y2 - 28 January 2011 through 30 January 2011
ER -