Population Based Training, Figure 2

Jupyter notebooks to play around with population based training, as described in https://arxiv.org/abs/1711.09846

Population Based Training (in PyTorch with sqlite3). Status: Unsupported

Article 1 code with bonus Population Based Training support

Curriculum training a Differentiable Neural Computer using Population Based Training

Implementation of the Google DeepMind paper introducing population-based training, except applied to simulated annealing instead of neural networks.

Reproducing results from DeepMind's paper on Population Based Training of Neural Networks.

Applying Population Based Training on Generative Adversarial Networks.

A simple PyTorch implementation of Population Based Training of Neural Networks.

Population-Based Training (PBT) implementation on ddpg

Implementation of the basic example of PBT in Rust from https://arxiv.org/abs/1711.09846

🥕 Mastering flappy bird with machine learning (neural networks, neuro-evolution)

My attempt to reproduce a water down version of PBT (Population based training) for MARL (Multi-agent reinforcement learning) using DDPPO (Decentralized & distributed proximal policy optimization) from ray[rllib].

Training in bursts for defending against adversarial policies

Optimize for topology, hyperparameters, and weights of Neural Nets in single joint training process using Augmented Population Based Training

Population-Based Training (PBT) for Reinforcement Learning using Message Passing Interface (MPI)

Vectorization techniques for fast population-based training.

A Population Based Reinforcement Learning Library based on PyTorch

Implementation of RPPO(Risk-sensitive PPO) and RPBT(Population-based self-play with RPPO)

Generating Evolutionary Opponents as a Reinforcement Guided Exploration Solution