Pinned Repositories
Active-Learning-for-Example-based-Dialog-Systems
Source files to replicate experiments in my IWSDS 2016 paper.
ConcreteDropout
Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832
Dialogue-State-Tracking-using-LSTM
Source files to replicate experiments in my IWSDS 2016 paper.
Dropout-Q-Functions-for-Doubly-Efficient-Reinforcement-Learning
Source files to replicate experiments in my ICLR 2022 paper.
Efficient-SRGC-RL-with-a-High-RR-and-Regularization
Source files to replicate experiments in my Arxiv 2023 paper.
Learning-Robust-Options-by-Conditional-Value-at-Risk-Optimization
Source files to replicate experiments in my NeurIPS 2019 paper.
Multi-Agent-Reinforcement-Learning-in-Stochastic-Games
Unofficial PyBrain extension for multi-agent reinforcement learning in general sum stochastic games.
Reinforcement-Learning-in-Multi-Party-Trading-Dialog
Source files to replicate experiments in my SigDial 2015 and JSAI papers.
Soft-Actor-Critic-and-Extensions
PyTorch implementation of Soft-Actor-Critic and Prioritized Experience Replay (PER) + Emphasizing Recent Experience (ERE) + Munchausen RL + D2RL and parallel Environments.
Which-Experiences-Are-Influential-for-RL-Agents
Source files to replicate experiments in my ArXiv 2024 paper.
TakuyaHiraoka's Repositories
TakuyaHiraoka/Dropout-Q-Functions-for-Doubly-Efficient-Reinforcement-Learning
Source files to replicate experiments in my ICLR 2022 paper.
TakuyaHiraoka/Efficient-SRGC-RL-with-a-High-RR-and-Regularization
Source files to replicate experiments in my Arxiv 2023 paper.
TakuyaHiraoka/Soft-Actor-Critic-and-Extensions
PyTorch implementation of Soft-Actor-Critic and Prioritized Experience Replay (PER) + Emphasizing Recent Experience (ERE) + Munchausen RL + D2RL and parallel Environments.
TakuyaHiraoka/Which-Experiences-Are-Influential-for-RL-Agents
Source files to replicate experiments in my ArXiv 2024 paper.
TakuyaHiraoka/d3rlpy
An offline deep reinforcement learning library
TakuyaHiraoka/d4rl
A benchmark for offline reinforcement learning.
TakuyaHiraoka/deep_bisim4control
Learning Invariant Representations for Reinforcement Learning without Reconstruction
TakuyaHiraoka/DiffRL
TakuyaHiraoka/dm_control
DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
TakuyaHiraoka/ElegantRL
Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥
TakuyaHiraoka/Eureka
TakuyaHiraoka/JARVIS
JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf
TakuyaHiraoka/mbrl-lib
Library for Model Based RL
TakuyaHiraoka/Meta-Model-Based-Meta-Policy-Optimization
Source files to replicate experiments in my ACML 2021 paper.
TakuyaHiraoka/metaworld
An open source robotics benchmark for meta- and multi-task reinforcement learning
TakuyaHiraoka/mopo
Code for MOPO: Model-based Offline Policy Optimization
TakuyaHiraoka/mujoco
Multi-Joint dynamics with Contact. A general purpose physics simulator.
TakuyaHiraoka/mujoco-maze
Simple maze environments using mujoco-py
TakuyaHiraoka/oyster
Implementation of Efficient Off-policy Meta-learning via Probabilistic Context Variables (PEARL)
TakuyaHiraoka/pianoplayer
Automatic fingering generator for piano scores
TakuyaHiraoka/pomdp-baselines
Simple (but often Strong) Baselines for POMDPs in PyTorch - ICML 2022
TakuyaHiraoka/ray
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
TakuyaHiraoka/REDQ
Author's PyTorch implementation of Randomized Ensembled Double Q-Learning (REDQ) algorithm.
TakuyaHiraoka/rltorch
A simple framework for distributed reinforcement learning in PyTorch.
TakuyaHiraoka/robopianist
🎹 🤖 A benchmark for high-dimensional robot control.
TakuyaHiraoka/robopianist-rl
TakuyaHiraoka/soft-actor-critic.pytorch
A PyTorch implementation of Soft Actor-Critic(SAC).
TakuyaHiraoka/SparseBaseline
TakuyaHiraoka/TakuyaHiraoka.github.io
TakuyaHiraoka/ToolBench
An open platform for training, serving, and evaluating large language model for tool learning.