Meta-reinforcement learning

Add to your list(s) Download to your calendar using vCal

• Kris Jensen and Calvin Kao (University of Cambridge)
• Wednesday 13 January 2021, 11:00-12:30
• https://eng-cam.zoom.us/j/86068703738?pwd=YnFleXFQOE1qR1h6Vmtwbno0LzFHdz09.

If you have a question about this talk, please contact Elre Oldewage.

Meta learning allows for generalisation across tasks and has become increasingly relevant as machine learning systems are asked to solve heterogeneous problems efficiently with less training data. In recent years, meta learning has been applied in the context of reinforcement learning to build agents that learn to generalise across a distribution of Markov decision problems. In this reading group, we will briefly introduce the basics of meta reinforcement learning, cover different approaches to the problem, and discuss their uses and limitations. We will also consider how they compare to more traditional algorithms, both learned and hand-crafted.

Recommended reading:

- Wang et al. 2016 (https://arxiv.org/abs/1611.05763) OR Duan et al. 2016 (https://arxiv.org/abs/1611.02779).

- Finn et al. 2017 (https://arxiv.org/abs/1703.03400). Nagabandi et al. 2019 (https://arxiv.org/abs/1803.11347).

- This blog post also provides an overview of several of the topics we will cover: https://lilianweng.github.io/lil-log/2019/06/23/meta-reinforcement-learning.html

This talk is part of the Machine Learning Reading Group @ CUED series.

This talk is included in these lists:

• All Talks (aka the CURE list)
• Cambridge Centre for Data-Driven Discovery (C2D3)
• Cambridge Forum of Science and Humanities
• Cambridge Language Sciences
• Cambridge University Engineering Department Talks
• Cambridge talks
• Centre for Smart Infrastructure & Construction
• Chris Davis' list
• Computational Continuum Mechanics Group Seminars
• Featured lists
• Guy Emerson's list
• Hanchen DaDaDash
• Inference Group Journal Clubs
• Inference Group Summary
• Information Engineering Division seminar list
• Interested Talks
• ML
• Machine Learning Reading Group
• Machine Learning Reading Group @ CUED
• Machine Learning Summary
• Quantum Matter Journal Club
• Required lists for MLG
• School of Technology
• Simon Baker's List
• TQS Journal Clubs
• Trust & Technology Initiative - interesting events
• bld31
• custom
• https://eng-cam.zoom.us/j/86068703738?pwd=YnFleXFQOE1qR1h6Vmtwbno0LzFHdz09
• ndk22's list
• ob366-ai4er
• rp587
• yk373's list

Note that ex-directory lists are not shown.