research
∙
01/09/2023
On The Fragility of Learned Reward Functions
Reward functions are notoriously difficult to specify, especially for ta...
share
research
∙
11/22/2022
imitation: Clean Imitation Learning Implementations
imitation provides open-source implementations of imitation and reward l...
research
∙
11/01/2022
Adversarial Policies Beat Professional-Level Go AIs
We attack the state-of-the-art Go-playing AI system, KataGo, by training...
research
∙
08/20/2022
Calculus on MDPs: Potential Shaping as a Gradient
In reinforcement learning, different reward functions can be equivalent ...
research
∙
08/10/2022
Reducing Exploitability with Population Based Training
Self-play reinforcement learning has achieved state-of-the-art, and ofte...
research
∙
03/25/2022
Preprocessing Reward Functions for Interpretability
In many real-world applications, the reward function is too complex to b...
research
∙
03/22/2022
A Primer on Maximum Causal Entropy Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) algorithms infer a reward function ...
research
∙
03/14/2022
Invariance in Policy Optimisation and Partial Identifiability in Reward Learning
It's challenging to design reward functions for complex, real-world task...
research
∙
03/14/2022
Uncertainty Estimation for Language Reward Models
Language models can learn a range of capabilities from unsupervised trai...
research
∙
12/10/2020
Understanding Learned Reward Functions
In many real-world tasks, it is not possible to procedurally specify an ...
research
∙
12/02/2020
DERAIL: Diagnostic Environments for Reward And Imitation Learning
The objective of many real-world tasks is complex and difficult to proce...
research
∙
06/24/2020
Quantifying Differences in Reward Functions
For many tasks, the reward function is too complex to be specified proce...
research
∙
05/25/2019
Adversarial Policies: Attacking Deep Reinforcement Learning
Deep reinforcement learning (RL) policies are known to be vulnerable to ...
research
∙
10/24/2018
Inverse reinforcement learning for video games
Deep reinforcement learning achieves superhuman performance in a range o...
research
∙
09/09/2018
Active Inverse Reward Design
Reward design, the problem of selecting an appropriate reward function f...
research
∙
05/22/2018
