… 1, “Introduction to Deep Reinforcement Learning,” … reinforcement learning is changing the
landscape of intelligent machines. It also covers the installation of Python and related libraries …

… open source library for carrying out reinforcement learning experiments in Python 2 and 3
… , reproducible methods for running reinforcement learning experiments. This paper gives an …

… deep reinforcement learning (DRL) library built using Python and the Chainer deep learning
… Keywords: reinforcement learning, deep reinforcement learning, reproducibility, open …

… Evaluating multiagent reinforcement learning (MARL) approaches in real world problems, …
In this paper, we introduce PyRL, a Python Reinforcement Learning Library that facilitates the …

… introduction to deep reinforcement learning covering the … looking to apply deep
reinforcement learning in practice.” … we will see in SLM Lab, the companion library to this book. …

… As you advance, you’ll delve into many novel algorithms with advanced implementations
using modern Python libraries such as TensorFlow and Ray/RLlib. You’ll also find out how to …

… , we demonstrate how to run Python’s scikit-learn, pytorch and OpenAI gym libraries for
building Machine Learning, Deep Learning, and Reinforcement Learning projects easily. …

… libraries used for reinforcement learning. Later in the chapter, we will see some of the
applications of reinforcement learning. … machine for various reinforcement learning tasks. We will …

… An alternative is to use Reinforcement Learning (RL) to generate the inputs by learning to …
In this work, we present VeRLPy [3], an open-source library to allow RL-driven verification with …

… In this paper, we introduce d3rlpy, an open-sourced offline deep reinforcement learning (RL)
library for Python. d3rlpy supports a set of offline deep RL algorithms as well as off-policy …