reinforcement learning – Page 4 – Andrew Fairless, Ph.D.

What I Read: Against Naive AI Scaling

By Andrew Fairless on July 27, 2022June 27, 2022

https://jacobbuckman.com/2022-06-14-an-actually-good-argument-against-naive-ai-scaling/ An Actually-Good Argument Against Naive AI ScalingJacob BuckmanPosted on June 14, 2022 “…the debate is whether scaled-up language models in the style of GPT-3 will eventually become general intelligences,Continue readingWhat I Read: Against Naive AI Scaling

What I Read: What is Reinforcement Learning

By Andrew Fairless on July 20, 2022June 27, 2022

https://castlelab.princeton.edu/what-is-rl/ What is Reinforcement LearningWarren B PowellProfessor Emeritus, Princeton University “…I provide a brief introduction to modeling sequential decision problems… and then designing policies. As I watch the evolution ofContinue readingWhat I Read: What is Reinforcement Learning

What I Read: Exploring Virtual Worlds, AI

By Andrew Fairless on July 14, 2022July 8, 2022

https://www.quantamagazine.org/ai-makes-strides-in-virtual-worlds-more-like-our-own-20220624/ By Exploring Virtual Worlds, AI Learns in New WaysAllison WhittenContributing WriterJune 24, 2022 “Intelligent beings learn by interacting with the world. Artificial intelligence researchers have adopted a similar strategyContinue readingWhat I Read: Exploring Virtual Worlds, AI

What I Read: Policy Regulariser, Adversary

By Andrew Fairless on May 11, 2022April 25, 2022

https://deepmindsafetyresearch.medium.com/your-policy-regulariser-is-secretly-an-adversary-14684c743d45 Your Policy Regulariser is Secretly an AdversaryDeepMind Safety ResearchMar 24 By Rob Brekelmans, Tim Genewein, Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Shane Legg, Pedro A. Ortega“Policy regularisation can beContinue readingWhat I Read: Policy Regulariser, Adversary

What I Read: To Understand Language is to Understand Generalization

By Andrew Fairless on February 16, 2022January 20, 2022

https://evjang.com/2021/12/17/lang-generalization.html To Understand Language is to Understand GeneralizationEric JangDec 17, 2021 “We all want ML models to generalize better, but defining “generalization” is hard. I suggest that the structure ofContinue readingWhat I Read: To Understand Language is to Understand Generalization

What I Read: How to Train Decision-Making AIs

By Andrew Fairless on February 8, 2022January 20, 2022

https://thegradient.pub/how-to-train-your-decision-making-ais/ How to Train your Decision-Making AIs10.Dec.2021Ruohan ZhangDhruva Bansal “How do humans transfer their knowledge and skills to artificial decision-making agents more efficiently? What kind of knowledge and skills shouldContinue readingWhat I Read: How to Train Decision-Making AIs

What I Read: Neural-Control Family

By Andrew Fairless on January 10, 2022December 11, 2021

https://www.gshi.me/blog/NeuralControl/ Neural-Control Family: What Deep Learning + Control Enables in the Real WorldGuanya Shi “…is machine learning (especially deep learning) really ready to be deployed in safety-critical systems?”

What I Read: Autonomous Building of Composable Models

By Andrew Fairless on December 1, 2021November 16, 2021

https://thegradient.pub/strong-ai-requires-autonomous-building-of-composable-models/ Strong AI Requires Autonomous Building of Composable Models30.Oct.2021Jonathan MuganDr. Jonathan Mugan is a principal scientist at DeUmbra and is the author of The Curiosity Cycle. “…AI must be ableContinue readingWhat I Read: Autonomous Building of Composable Models

What I Learn: Robots Must Be Ephemeralized

By Andrew Fairless on October 11, 2021September 24, 2021

https://blog.evjang.com/2021/09/ephemeralization.html Robots Must Be EphemeralizedEric JangMonday, September 20, 2021 “I now believe that offline evaluation technology is no longer optional if you are studying general-purpose robots… I outline why itContinue readingWhat I Learn: Robots Must Be Ephemeralized

What I Read: Permutation-Invariant Neural Networks for Reinforcement Learning

By Andrew Fairless on October 5, 2021September 21, 2021

https://arxiv.org/abs/2109.02869v1 The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for Reinforcement LearningYujin Tang, David Ha “…we build systems that feed each sensory input from the environment into distinct, butContinue readingWhat I Read: Permutation-Invariant Neural Networks for Reinforcement Learning

Tag: reinforcement learning