Josh Hoffman's Projects
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).
The final code submission for CS 393r HW1 - Obstacle avoidance.
This is my group's project for Hack Beanpot 2018.
This is a copy of a school project for the organization Generation Citizen. We created a mobile up using ReactNative for a front end, and Node.JS for our backend.
A place to playground with new go architectures and ideas
A group project recommender built in Python Flask + mysql
This is my first repository!
Code for hierarchical imitation learning and reinforcement learning
A workspace for doing interview prep in GoLang
A collection of technical Interview questions and solutions
Config files for my GitHub profile.
Personal website
Level-based Foraging (LBF): A multi-agent environment for RL
Inference code for LLaMA models
This is the package for a gazebo simulation of two TurtleBots and a Fetch robot
A Multi-agent reinforcement-learning simulator framework.
Modular multitask reinforcement learning with policy sketches
Tools for accelerating safe exploration research.
Basic constrained RL agents used in experiments for the "Benchmarking Safe Exploration in Deep Reinforcement Learning" paper.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent