research
∙
03/05/2021
Causal Analysis of Agent Behavior for AI Safety
As machine learning systems become more powerful they also become increa...
share
research
∙
10/23/2020
Algorithms for Causal Reasoning in Probability Trees
Probability trees are one of the simplest models of causal generative pr...
research
∙
10/21/2020
Meta-trained agents implement Bayes-optimal agents
Memory-based meta-learning is a powerful technique to build agents that ...
research
∙
10/15/2020
Avoiding Side Effects By Considering Future Tasks
Designing reward functions is difficult: the designer has to specify wha...
research
∙
12/14/2018
Scaling shared model governance via model splitting
Currently the only techniques for sharing governance of a deep learning ...
research
∙
11/19/2018
Scalable agent alignment via reward modeling: a research direction
One obstacle to applying reinforcement learning algorithms to real-world...
research
∙
06/04/2018
Measuring and avoiding side effects using relative reachability
How can we design reinforcement learning agents that avoid causing unnec...
research
∙
11/27/2017
AI Safety Gridworlds
We present a suite of reinforcement learning environments illustrating v...
research
∙
06/12/2017