Dr. Hector Munoz-Avila conducts research on case-based reasoning, planning, and machine learning. He is also interested in advancing game AI with AI techniques. His primary research interest falls in the intersection of Case-based Reasoning (CBR) and Automated Planning, with an eye into applied AI research topics (see his invited talk at ICCBR-03). CBR is a problem-solving methodology by which previous problem-solving experiences (called cases) are reused to solve new problems.

His research team is particularly interested in the following topics:

• Applied AI research
  
  • Knowledge-based Project Planning
  • Interactive Entertainment Systems (i.e., computer games) and AI
  • Plan Discovery
• Formal Foundations of CBR
• Learning Hierarchical Task Networks (HTNs)

Dr. Munoz-Avila lab has received funding from the National Science Fundation (NSF) and the Air Force Research Laboratory (AFRL), as well as the Defense Advanced Research Projects Agency (DARPA), the Office of Naval Research (ONR), and the Naval Research Laboratory (NRL). He is a recipient of the National Science Foundation (NSF) CAREER award and two papers awards. He has served as chair for various international scientific meetings, including the Sixth International Conference on Case-Based Reasoning (ICCBR-05).