<aside> 💡 Hi! I'm a PhD student at the University of Oxford working on Multitask Reinforcement Learning in Graph-Based environments with Shimon Whiteson. I read and take notes of the papers I read. I hope they might be helpful to you (please, share, if they are). I add a paper every day Monday-Friday. Ping me on twitter.

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• Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
• Task-Agnostic Morphology Evolution
• Lifelong Learning with a Changing Action Set
• The frontier of simulation-based inference
• Semi-parametric Topological Memory for Navigation
• Decoupling Value and Policy for Generalization in Reinforcement Learning
• Neural Algorithmic Reasoning

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• When to use parametric models in reinforcement learning?
• Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization
• Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments
• Inductive Representation Learning on Large Graphs
• Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning
• Learning and Planning in Complex Action Spaces
• Observational Overfitting in Reinforcement Learning
• SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks
• Learning Deep Generative Models of Graphs
• Learning Dynamic Belief Graphs to Generalize on Text-Based Games