An Anarchy of Methods: Current Trends in How AI is Abstracted in AI (2014)
Joel Lehman, Jeff Clune and Sebastian Risi
Artificial intelligence (AI) is a sprawling field encompassing a diversity of approaches to machine intelligence and disparate perspectives on how intelligence should be viewed. Because researchers often engage only within their own specialized area of AI, there are many interesting broad questions about AI as a whole that often go unanswered. How should intelligence be abstracted in AI research? Which subfields, techniques, and abstractions are most promising? Why do researchers bet their careers on the particular abstractions and techniques of their chosen subfield of AI? Should AI research be “bio-inspired” and remain faithful to the process that produced intelligence (evolution) or the biological substrate that enables it (networks of neurons)? Discussing these big-picture questions motivated us to organize an AAAI Fall Symposium, which gathered participants across AI subfields to present and debate their views. This article distills the resulting insights.
Intelligent Systems magazine, 29(6):56-62, 2014.

Joel Lehman Postdoctoral Alumni joel [at] cs utexas edu