Patrick R. Jordan

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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)
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)
I describe a research effort for developing empirical methods for practical strategic reasoning and analysis, with applications in market scenarios. These market scenarios typically form dynamic games with severely incomplete and imperfect information. In cases where exact analytical models of a game cannot be constructed, empirical game-theoretic models(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)
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.
ABSTRACT 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(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)
Empirical analyses of complex games necessarily focus on a restricted set of strategies, and thus the value of empirical game models depends on effective methods for selectively exploring a space of strategies. We formulate an iterative framework for strategy exploration, and experimentally evaluate an array of generic exploration policies on three games:(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)