#81 JULIAN TOGELIUS, Prof. KEN STANLEY - AGI, Games, Diversity & Creativity [UNPLUGGED] episode artwork

EPISODE · Nov 20, 2022 · 1H 9M

#81 JULIAN TOGELIUS, Prof. KEN STANLEY - AGI, Games, Diversity & Creativity [UNPLUGGED]

from Machine Learning Street Talk (MLST)

Support us (and please rate on podcast app) https://www.patreon.com/mlst  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

Episode metadata supplied by the publisher feed · Published Nov 20, 2022

Embed this episode

NOW PLAYING

#81 JULIAN TOGELIUS, Prof. KEN STANLEY - AGI, Games, Diversity & Creativity [UNPLUGGED]

0:00 1:09:46

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

No similar episodes found.

Frequently Asked Questions

How long is this episode of Machine Learning Street Talk (MLST)?

This episode is 1 hour and 9 minutes long.

When was this Machine Learning Street Talk (MLST) episode published?

This episode was published on November 20, 2022.

Can I download this Machine Learning Street Talk (MLST) episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!