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Hector Munoz-Avila

Selected Invited Talks

  • AAAI Fall Symposium on Artificial Intelligence for Synthetic Biology. Introduction to AI and ML. Washington DC, October, 2018

  • Naval Research Laboratory, Navy Center for Applied Research in Artificial Intelligence's seminar series. Automated Learning of Hierarchical Task Network Knowledge. Washington DC, August, 2018.

  • Knexus Corporation. Machine Learning for Eliciting Hierarchical Task Networks (HTNs). Washington DC, August, 2018.

  • 26th International Conference on Case-based Reasoning (ICCBR-18). Adaptive Goal Driven Autonomy. Stockholm, Sweden. July, 2018.

  • Joint National Science Foundation - Japan Science and Technology Agency Symposium. Towards High-Level Autonomy with Cognitive Systems and (Big) Data. November, 2016. Tokyo, Japan.

  • University of Alberta. Invited Lecture. Informed expectations: Balancing Agentsí Self-Monitoring Commitments and Sensing Costs. May, 2016. Edmonton, Canada.

  • Georgia Institute of Technology. Raising Expectations: Self-Monitoring Goal-Driven Autonomy Agents. January, 2016. Atlanta, GA.

  • ICCBR-15 Workshop on Case-Based Agents. Towards Scalable Autonomous Agents for Real-Time Strategy Games. September 2015. Frankfurt, Germany.

  • University of Trondheim (NTNU). Goal-Driven Autonomy: Reflective learning for Real-Time Strategy Games. March, 2014. Trondheim, Norway.

  • Huazhong University of Science and Technology, HTN learning and HTN adaptation, December, 2012. Wuhan, China.

  • Lafayette College. Goal-Driven Autonomy. November, 2011. Easton, PA

  • ICCBR-11 Workshop on Case-Based Reasoning for Computer Games. A Case Study for Generating Strategic Game AI: From HTN Planning to Multi-Modal Learning. London, UK.

  • Universidad Carlos III de Madrid. Learning Hierarchical Task Networks: Instance-based, Non-deterministic, and Optimality studies February, 2010: Madrid, Spain

  • Universidad Carlos III de Madrid. Game AI through HTN Planning, Case-based Reasoning, and Reinforcement learning: a comparative study February, 2010: Madrid, Spain

  • Universidad Complutense de Madrid. Learning Hierarchical Task Networks February, 2010: Madrid, Spain

  • SET Corporation. An Overview of Case-Based Reasoning and Current research Directions. July, 2009: Washington, DC.

  • SET Corporation. A Case Study of Online Adaptive AI for a Real-Tme Game. July, 2008: Washington, DC.

  • Hong Kong University of Science and technology. Learning preconditions and Structure of Hierarchical Task Networks: an Overview. May, 2008: Hong Kong, China.

  • National Tsing Hua University. Two Case Studies of Adaptive AI in Team-based First Person Shooter (FPS) Games. June, 2007: HsinChu, Taiwan.

  • National Taiwan University. Automated Planning and Learning of Adaptive AI in Team-Based First Person Shooter (FPS) Games. June, 2007: Taipei, Taiwan.

  • The Rutgers Laboratory for Real-Life Reinforcement Learning. Hierarchical Task Network Planning and Learning. August, 2006: New Jersey, USA

  • Army Research Laboratory Workshop on Knowledge Fusion. OntoPlan: Knowledge Fusion Using Semantic Web Ontologies. October, 2004: Maryland, USA

  • Naval Research Laboratory. Universal SiN: Integrating Planning and Case-Based Reasoning in an Universal Classical Planning Framework. October, 2003: Washington, DC, USA

  • Fifth International Conference on Case-based Reasoning (ICCBR-03). On the Role of Cases in Case-Based Planning. July, 2003: Trondheim, Norway.

  • Lockheed Martin Advanced Technology Laboratories. Integrating HTN Planning and Case-Based Reasoning. August, 2001: Camden, New Jersey, USA.


© 2003 P.C. Rossin College of Engineering & Applied Science
Computer Science & Engineering, Packard Laboratory, Lehigh University, Bethlehem PA 18015