Learning is a key component to the successful application of intelligent physical and virtual agents in everyday human environments.  Research in interactive learning focuses on enabling agents to learn from teachers the way that people do.

Building models of human-like learning is important for both engineering and scientific reasons.  It is impossible to give machines all of the knowledge and skills a priori that they will need to serve useful long term roles in our dynamic world. If humans and machines are to work together in challenging environments, then machines must be able to learn quickly from any knowledgeable human, not just expert programmers.  The environments in which humans act are highly diverse and constantly changing — whether in the office, at home, or alongside a soldier. Even a machine with exhaustive background knowledge must be customized for the particular environment in which it acts.

The goal of this AAMAS 2010 workshop is to increase awareness and interest in interactive learning methods and to foster collaboration between researchers across many disciplines.  We are seeking broad participation from researchers in the areas of:

1. •Artificial Intelligence
   

2. •Learning from Demonstration
   

3. •Teachable Agents
   

4. •Education
   

5. •Human-Computer Interaction
   

6. •Human-Robot Interaction
   

7. •Intelligent User Interfaces
   

8. •Developmental Psychology
   

9. •Adaptive systems
   

10. •Cognitive Science
    

11. •Computer Games
    

12. •Other related fields