Model-Based-Reinforcement-Learning

Huawei-Edinburgh Joint Lab: Discrete Codebook World Models

Nordic AI Meet & AI Day: Sample-efficient Reinforcement Learning with Implicitly Quantized Representations

Model-Based Reinforcement Learning

I'll be giving a lecture on model-based RL at the Cambridge Ellis Unit Summer School on Probabilistic Machine Learning 2024.

Function-Space Bayesian Deep Learning for Sequential Learning

Sequential learning paradigms pose challenges for gradient-based deep learning due to difficulties incorporating new data and retaining prior knowledge. While Gaussian processes …

Neural Networks as Sparse Gaussian Processes for Sequential Learning

I will be presenting our research on bayesian deep learning for sequential learning at the [International Workshop of Intelligent Autonomous Learning Systems …

Mode-constrained Model-based Reinforcement Learning via Gaussian Processes

We present a model-based RL algorithm that constrains training to a single dynamic mode with high probability. This is a difficult problem because the mode constraint is a hidden …

Aidan Scannell

• 27 Apr, 2023 • 1 min read

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Model-based reinforcement learning under uncertainty

Investigating Bayesian Neural Network Dynamics Models for Model-Based Reinforcement Learning

This project seeks to evaluate and compare different approaches for learning dynamics models in model-based RL. In particular, we plan to compare different approximate inference …

Model-based reinforcement learning under uncertainty: the importance of knowing what you don't know