Open Source Robotic Simulators Platforms for Teaching Deep Reinforcement Learning Algorithms

摘要

One of the primary goals of the artificial intelligence field is to produce fully autonomous agents that interact with theirenvironments to learn optimal behaviors, improving over time through trial and error. A mathematical principled framework for experience-driven autonomous learning is reinforcement learning, but they are inherently limited to low-dimensional problems,but the deep learning boom has provided new tools to overcome these problems. For deep reinforcement learning teaching, we do not have an appropriate platform for making optimal labs. In the article, after studying the theoretical foundations and the requirements of the main platforms, we selected two open source platforms, according to their characteristics: robotic simulators platforms for teaching and benchmarking deep reinforcement learning algorithms. The first platform was Gym and V-REP and the second one, KNIME Deeplearning4J Integration supports and Teaching-Box.