Takuya Hiraoka's repositories
tensor2robot
Distributed machine learning infrastructure for large-scale robotics research
mbpo
Code for the paper "When to Trust Your Model: Model-Based Policy Optimization"
Learning-Robust-Options-by-Conditional-Value-at-Risk-Optimization
Source files to replicate experiments in my NeurIPS 2019 paper.
snail-pytorch
Implementation of "A Simple Neural Attentive Meta-Learner" (SNAIL, https://arxiv.org/pdf/1707.03141.pdf) in PyTorch
learning_to_adapt
Learning to Adapt in Dynamic, Real-World Environment through Meta-Reinforcement Learning
PPOC
Proximal Policy Option-Critic
gym-extensions
This repo is intended as an extension for OpenAI Gym for auxiliary tasks (multitask learning, transfer learning, inverse reinforcement learning, etc.)
ConcreteDropout
Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832
rllab
rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.
naacl18-multitask_argument_mining
Code for the paper "Multi-Task Learning for Argumentation Mining in Low-Resource Settings"
gamepad
A Learning Environment for Theorem Proving
marseille
Mining Argument Structures with Expressive Inference (Linear and LSTM Engines)
Grounded-Language-Learning-in-Pytorch
Implementation of Grounded Language Learning in a 3D Simulated World (DeepMind)
Reinforcement-Learning-in-Multi-Party-Trading-Dialog
Source files to replicate experiments in my SigDial 2015 and JSAI papers.
Dialogue-State-Tracking-using-LSTM
Source files to replicate experiments in my IWSDS 2016 paper.
robustRL
Robust policy search algorithms which train on model ensembles
Multi-Agent-Reinforcement-Learning-in-Stochastic-Games
Unofficial PyBrain extension for multi-agent reinforcement learning in general sum stochastic games.
Active-Learning-for-Example-based-Dialog-Systems
Source files to replicate experiments in my IWSDS 2016 paper.