011235813 Goto Github PK
Name: Jiachen Yang
Type: User
Bio: Researcher in multi-agent deep reinforcement learning and AI for science. Ph.D. in Machine Learning from Georgia Institute of Technology.
Jiachen Yang's Projects
ai-economist
Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).
cm3
Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning
discrete_mean_field_game
Experiments on a discrete mean field game model of population dynamics with reinforcement learning
graph_nets
Build Graph Nets in Tensorflow
hierarchical-marl
Hierarchical Cooperative Multi-Agent Reinforcement Learning with Skill Discovery
higgs_ml
Classifier for Higgs dataset
lio
Learning to Incentivize Other Learning Agents
llnl.github.io
Public home for LLNL software catalog
lola
Code release for Learning with Opponent-Learning Awareness and variations.
metagradient-incentive-design
Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning
pinterest_api
Pinterest API using Python
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.
rlbot_twitter
Data collection and experiment framework based on Tweepy
rljax
A collection of RL algorithms written in JAX.
sept
Single Episode Policy Transfer in Reinforcement Learning
sequential_social_dilemma_games
Repo for reproduction of sequential social dilemmas
tensorflow
Computation using data flow graphs for scalable machine learning
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