Naturally Inspired AI: Papers from the AAAI Fall Symposium
Jacob Beal, Paul Bello, Nick Cassimatis, Michael Coen, and Patrick Winston, Cochairs
The divide between how biological and computational systems solve cognitive problems and adjust to novel circumstances is readily apparent. While animals display marked flexibility in adjusting to new situations, our current computational approaches excel in well-defined, formally structured domains. We are interested in new approaches to bridging this gap. Our perspective is that studies of natural and artificial intelligences can and should be mutually informative. Even young animals solve historically difficult computational problems, and we believe understanding how they do this will enable the creation of more sophisticated artificial systems. Conversely, computational models provide structure and insight into understanding animal learning and cognition. By combining biological and computational perspectives, we expect to obtain new insights that further the classical goals of artificial intelligence.