Ketter, Wolfgang


Competitive Benchmarking: Lessons Learned from the Trading Agent Competition

AI Magazine

Over the years, competitions have been important catalysts for progress in artificial intelligence. We describe the goal of the overall Trading Agent Competition and highlight particular competitions. We discuss its significance in the context of today's global market economy as well as AI research, the ways in which it breaks away from limiting assumptions made in prior work, and some of the advances it has engendered over the past ten years. Since its introduction in 2000, TAC has attracted more than 350 entries and brought together researchers from AI and beyond.


Pushing the Limits of Rational Agents: The Trading Agent Competition for Supply Chain Management

AI Magazine

Over the years, competitions have been important catalysts for progress in Artificial Intelligence. We describe one such competition, the Trading Agent Competition for Supply Chain Management (TAC SCM). We discuss its significance in the context of today's global market economy as well as AI research, the ways in which it breaks away from limiting assumptions made in prior work, and some of the advances it has engendered over the past six years. TAC SCM requires autonomous supply chain entities, modeled as agents, to coordinate their internal operations while concurrently trading in multiple dynamic and highly competitive markets.


AAAI 2008 Workshop Reports

AI Magazine

The program included the following fifteen workshops: Advancements in POMDP Solvers, AI Education Workshop, Coordination, Organization, Institutions and Norms in Agent Systems, Enhanced Messaging, Human Implications of Human-Robot Interaction, Intelligent Techniques for Web Personalization and Recommender Systems, Metareasoning: Thinking about Thinking, Multidisciplinary Workshop on Advances in Preference Handling, Search in Artificial Intelligence and Robotics, Spatial and Temporal Reasoning, Trading Agent Design and Analysis, Transfer Learning for Complex Tasks, What Went Wrong and Why: Lessons from AI Research and Applications, and Wikipedia and Artificial Intelligence: An Evolving Synergy. The goal of the Coordination, Organizations, Institutions and Norms in Multiagent Systems workshop was to examine and define the current state of the art research in agent systems research related to coordination, organizations institutions and norming. The Intelligent Techniques for Web Personalization and Recommender Systems workshop was scheduled as a joint event, bringing together researchers and practitioners from the fields of web personalization and recommender systems. The Search in Artificial Intelligence and Robotics workshop brought together search researchers to share their ideas and disseminate their latest research results.