My main research interest is in the old-fashioned goal of Artificial Intelligence, that of building autonomous agents that can learn by interaction in complex, dynamic, and uncertain environments.

My deepest interest and contributions are in the area of reinforcement learning (RL). Ongoing projects in RL are:

• Predictive Representations of State (PSRs)
• Intrinsically Motivated Reinforcement Learning
• Transfer Across RL Tasks

More recently, I have been taking seriously the challenge of building agents that can interact with other agents and even humans in both artificial and natural environments. This has led to research in

1. Computational Game Theory with the following projects
• Graphical Games with Private Information
• (OLD) Trading Agent Competition (Supply Chain Management)
2. Mechanism Design with the following projects
• Online Mechanism Design
• Learning in Online Mechanism Design
• Market of Minds
3. Human Computer Interaction with the following projects:
• (OLD) Adaptive Cognitive Orthotics

My Students and Research Group Pages