Agents that Reason and Learn

This talk will address the issue of designing architectures for agents that need to be able to adapt to changing circumstances during deployment. From a scientific point of view, the primary challenge is to design agent architectures that seamlessly integrate reasoning and learning capabilities. That this is indeed a challenge is largely due to the fact that reasoning and knowledge representation capabilities of agents are studied in different subfields of computer science from the subfields in which learning for agents is studied. So far there have been few attempts to integrate these two research themes. In any case, agent architectures is very much an open issue with plenty of scope for new ideas.