Raphael Avalos's repositories

attention_tsp_graph_net

Implementation of Attention Solves Your TSP, Approximately (W. Kool et al.) with the DeepMind's Graph Nets library

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coma_rllib

Implentation of COMA using RLlib.

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maac_rllib

RLlib implementation of Iqbal and Sha "Actor-Attention-Critic for Multi-Agent Reinforcement Learning" 2019.

gym-rubikscube

Gym Environment for the Rubik's Cube

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aml-lab

This repository contains the labs of AML course at Eurecom (Spring 2018). Those labs are done with Hugo Yeche. (Mirror repository of bitbucket)

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CGT-assignment-3-2

VUB CGT assignement 3 - 2nd session

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deepRL-doom

Implementation of Learning to Act by Predicting the Future (Alexey Dosovitskiy, Vladlen Koltun)

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ray

A fast and simple framework for building and running distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

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CGT2022-assignment-3

VUB CGT 2022 assignement 3

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flow

Computational framework for reinforcement learning in traffic control

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gotify-server

A simple server for sending and receiving messages in real-time per WebSocket. (Includes a sleek web-ui)

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jumanji

🕹️ A diverse suite of scalable reinforcement learning environments in JAX

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mlflow

Open source platform for the machine learning lifecycle

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multiagent-particle-envs

Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

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mva-deep-learning

Homework for DeepLearning class of Vincent Lepetit

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PettingZoo

Gym for multi-agent reinforcement learning

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probabilistic-graphical-models

Probabilistic Graphical Models

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Radicale

A simple CalDAV (calendar) and CardDAV (contact) server.

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rl

RL experiments

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rlpyt

Reinforcement Learning in PyTorch

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RODE

Codes accompanying the paper "RODE: Learning Roles to Decompose Multi-Agent Tasks (ICLR 2021, https://arxiv.org/abs/2010.01523). RODE is a scalable role-based multi-agent learning method which effectively discovers roles based on joint action space decomposition according to action effects, establishing a new state of the art on the StarCraft multi-agent benchmark.

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vaia_rl

VAIA RL course and tutorial.

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