jachiam / surpriseLinks
Surprise-based intrinsic motivation for deep reinforcement learning
☆20Updated 8 years ago
Alternatives and similar repositories for surprise
Users that are interested in surprise are comparing it to the libraries listed below
Sorting:
- Proximal Policy Optimization with Stein Control Variates:☆33Updated 7 years ago
- Implementation of Deepmind's Neural Episodic Control☆58Updated 7 years ago
- Exploration Strategies for Deep Reinforcement Learning☆39Updated 6 years ago
- A Tensorflow implementation of Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning☆32Updated 7 years ago
- Stochastic Neural Networks for Hierarchical Reinforcement Learning☆95Updated 7 years ago
- Simple tools for statistical analyses in RL experiments☆67Updated 7 years ago
- ☆44Updated 6 years ago
- Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees☆93Updated 5 years ago
- Accompanying code for "Deep Reinforcement Learning that Matters"☆153Updated 7 years ago
- This is my implementation of the Optimality Tightening☆37Updated 8 years ago
- Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning☆80Updated 7 years ago
- Model-Based Generative Adversarial Imitation Learning☆89Updated 4 years ago
- ☆43Updated 8 years ago
- Explore the optimization landscape for direct policy learning reinforcement learning.☆51Updated 6 years ago
- Machine Learning Course Project Skoltech 2018☆108Updated 6 years ago
- Model-Free-Episodic-Control implementation.☆17Updated 6 years ago
- SeqGAN but with more bells and whistles☆24Updated 7 years ago
- ☆35Updated 7 years ago
- TensorFlow impementation of: Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images☆64Updated 9 years ago
- Code for experimenting with state and action abstractions in reinforcement learning.☆30Updated 4 years ago
- This repository contains code for the method and experiments of the paper "Learning with AMIGo: Adversarially Motivated Intrinsic Goals".☆63Updated last year
- PGQ is an approach to combine Policy Gradient and Q-Learning. This repository will contain an implementation of PGQ.☆15Updated 8 years ago
- Ant Gather and Ant Maze envs, separated from RLLab☆11Updated 7 years ago
- Code for paper "Learning Multimodal Transition Dynamics for Model-Based Reinforcement Learning".☆35Updated 7 years ago
- A parallel version of Trust Region Policy Optimization☆65Updated 8 years ago
- [NeurIPS 2019] Code for the paper "Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity"☆116Updated 5 years ago
- Robust policy search algorithms which train on model ensembles☆30Updated 8 years ago
- PyTorch implementation of Memory Augmented Self-Play☆52Updated 4 years ago
- Code for the paper "TD or not TD: Analyzing the Role of Temporal Differencing in Deep Reinforcement Learning", Artemij Amiranashvili, Ale…☆12Updated 7 years ago
- A working implementation of the Categorical DQN (Distributional RL).☆96Updated 7 years ago