IlliGAL Blogging

Lashon is talking about the early days in the 70s and 80s of irrational exuberance about artificial intelligence and how Holland couldn't understand how symbolic AIers were going to avoid brittleness.

Needs then:

• exploit regularities in the environments
• generalizations selective, pragmatic, and subject to exceptions
• learning must be incremental and coupled to performance
• rules as tentative hypotheses, not consistent assertions

Classifiers evolved from those early days with a strong emphasis on cognition. Reinforcement learning came along (with roots out of UofM) and gave important formalism.

Lashon wonders if we are solving problems that take advantage of what classifier systems do well and how to describe the architecture of classifier systems that will. He contrasted LCSs with the success of SOAR in solving problems and becoming more widely accepted.

After break Martin Butz is up next.