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We present and evaluate the design of Deep Maize, our entry in the 2005 Trading Agent Competition Supply Chain Management scenario. The central idea is to decompose the problem by estimating the value of key resources in the game. We first create a high-level production schedule that considers cross-cutting constraints and future decisions, but abstracts(More)
We introduce the TAC Ad Auctions game (TAC/AA), a new game for the Trading Agent Competition. The Ad Auctions game investigates complex strategic issues found in real sponsored search auctions that are not captured in current analytical models. We provide an overview of TAC/AA, introducing its key features and design rationale. TAC/AA will debut in summer(More)
Future market conditions can be a pivotal factor in making business decisions. We present and evaluate methods used by our agent, Deep Maize, to forecast market prices in the Trading Agent Competition Supply Chain Management Game. As a guiding principle we seek to exploit as many sources of available information as possible to inform predictions. Since(More)
The holy grail of online advertising is to target users with ads matched to their needs with such precision that the users respond to the ads, thereby increasing both advertisers' and users' value. The current approach to this challenge utilizes information about the users: their gender, their location, the websites they have visited before, and so on.(More)
We illustrate developing techniques for empirical game-theoretic analysis by application to two challenging market games employed in an annual Trading Agent Competition. These games exemplify relevant environments beyond analytic tractability, yet which can be investigated experimentally through simulation and careful measurement. Our analysis of agents(More)
The TAC SCM tournament is moving into its fourth year. In an effort to track agent progress, we present a benchmark market efficiency comparison for the tournament, in addition to prior measures of agent competency through customer bidding. Using these benchmarks we find statistically significant increases in intratournament market efficiency , whereas(More)
When exploring a game over a large strategy space, it may not be feasible or cost-effective to evaluate the payoff of every relevant strategy profile. For example, evaluating each payoff of an empirically defined game may require Monte Carlo simulation or other costly computation. Analyzing such games poses a search problem, with the goal of identifying and(More)
The TAC Supply Chain Management (TAC/SCM) game presents a challenging dynamic environment for autonomous decision-making in a salient application domain. Strategic interactions complicate the analysis of games such as TAC/SCM. since the effectiveness of a given strategy depends on the strategies played by other agents on the supply chain. The TAC tournament(More)
When exploring a game over a large strategy space, it may not be feasible or cost-effective to evaluate the payoff of every relevant strategy profile. For example, determining a profile payoff for a procedurally defined game may require Monte Carlo simulation or other costly computation. Analyzing such games poses a search problem, with the goal of(More)
We specify the Trading Agent Competition Ad Auction game (TAC/AA), a new TAC market game in the domain of sponsored search. Agents play the role of search engine advertisers, who compete with each other on ad placement for search results. The final round of the TAC/AA tournament will be held in Pasadena in July in conjunction with IJCAI 2009.