Meeting Summary: This workshop will follow up on the March workshop organized by the NSF-funded program “Foundations of Intelligence in Natural and Artificial Systems.” The March workshop introduced a number of important research themes central to this program, including the success of biological evolution in designing intelligent systems and the potential value of employing evolutionary computation in artificial intelligence. The workshop will focus on identifying barriers to scaling up evolutionary computation and in understanding how existing approaches to evolutionary computation might be augmented to overcome those barriers. More specifically, we are interested in understanding the relationship between biological evolution and evolutionary computation as well as the role of neuro-evolution, recombination, co-evolution, open-endedness, and learning in evolutionary computation. Specific questions to be addressed include the following:
• What important elements of biological evolution are missing in EC?
• What opportunities/difficulties come with increases in computational power?
• What kind of intelligence is exhibited by evolution as a design process?
• How do evolved and designed systems differ?
• How can co-evolution benefit EC and machine learning?
• Can EC contribute to our understanding of biological evolution?
• What is the role (if any) of recombination in EC?