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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

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