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In this show tonight with Prof. Julian Togelius (NYU) and Prof. Ken Stanley we discuss open-endedness, AGI, game AI and reinforcement learning.
[Prof Julian Togelius]
https://engineering.nyu.edu/faculty/julian-togelius
https://twitter.com/togelius
[Prof Ken Stanley]
https://www.cs.ucf.edu/~kstanley/
https://twitter.com/kenneth0stanley
TOC:
[00:00:00] Introduction
[00:01:07] AI and computer games
[00:12:23] Intelligence
[00:21:27] Intelligence Explosion
[00:25:37] What should we be aspiring towards?
[00:29:14] Should AI contribute to culture?
[00:32:12] On creativity and open-endedness
[00:36:11] RL overfitting
[00:44:02] Diversity preservation
[00:51:18] Empiricism vs rationalism , in gradient descent the data pushes you around
[00:55:49] Creativity and interestingness (does complexity / information increase)
[01:03:20] What does a population give us?
[01:05:58] Emergence / generalisation snobbery
References;
[Hutter/Legg] Universal Intelligence: A Definition of Machine Intelligence
https://arxiv.org/abs/0712.3329
https://en.wikipedia.org/wiki/Artificial_general_intelligence
https://en.wikipedia.org/wiki/I._J._Good
https://en.wikipedia.org/wiki/G%C3%B6del_machine
[Chollet] Impossibility of intelligence explosion
https://medium.com/@francois.chollet/the-impossibility-of-intelligence-explosion-5be4a9eda6ec
[Alex Irpan] - RL is hard
https://www.alexirpan.com/2018/02/14/rl-hard.html
https://nethackchallenge.com/
Map elites
https://arxiv.org/abs/1504.04909
Covariance Matrix Adaptation for the Rapid Illumination of Behavior Space
https://arxiv.org/abs/1912.02400
[Stanley] - Why greatness cannot be planned
https://www.amazon.com/Why-Greatness-Cannot-Planned-Objective/dp/3319155237
[Lehman/Stanley] Abandoning Objectives: Evolution through the Search for Novelty Alone
https://www.cs.swarthmore.edu/~meeden/DevelopmentalRobotics/lehman_ecj11.pdf
