While looking for architectures that decode electroencephalography without discarding either its timing or its spatial structure, I came across the … More
Tag: paper digest
Identifying Sentiment-based Contradictions
Consulting other people’s opinions refines our own and helps us choose. Extracting useful information from those opinions, product reviews for … More
Counterfactually-Guided Policy Search
A compelling way to reduce the cost of real experience in reinforcement learning is to learn policies on data synthesised … More
Inverse Reinforcement Learning from a Gradient-based Learner
While searching for gradient based approaches in Inverse Reinforcement Learning, I came across the recent contribution of Ramponi et al. … More
Learning Rewards from Linguistic Feedback
While discussing with my supervisor about how to move forward with our project, he suggested me to look at the … More
Bayesian Inverse Reinforcement Learning
In the last couple of months I have been studying Inverse Reinforcement Learning approaches, in particular the work of Ramachandran … More
Learning to Summarize with Human Feedback
Interesting blog article and diagram from OpenAI.
Dealing with Opponents in Multi-Agent System
As a step towards efficient transfer learning between two opponent agents, my colleagues and I encountered one of the most … More
Developmental Robotics and Reinforcement Learning: Glossary
Moravec’s paradox: “The deliberate process we call reasoning is, I believe, the thinnest veneer of human thought, effective only because … More
Learning with Opponent-Learning Awareness
Learning with Opponent-Learning Awareness (LOLA), introduced by Foerster et al. in 2018, has each agent take into account the anticipated … More
