文章作者: Arthur Juliani

ML-Agents Toolkit v0.5, new resources for AI researchers available now

We are committed to working to help make Unity the go-to platform for Artificial Intelligence (AI) research. In the past few weeks, we’ve se... 阅读更多

+1 九月 11, 20184

Solving sparse-reward tasks with Curiosity

We just released the new version of ML-Agents toolkit (v0.4), and one of the new features we are excited to share with everyone is the abili... 阅读更多

六月 26, 201817

Unity ML-Agents Toolkit v0.4 and Udacity Deep Reinforcement Learning Nanodegree

We are happy to announce the release of the latest version of ML-Agents Toolkit: v0.4. It contains a number of features, which we hope every... 阅读更多

六月 19, 201815

ML-Agents Toolkit v0.3 Beta released: Imitation Learning, feedback-driven features, and more

We are happy to announce that the ML-Agents team is releasing the latest version of our toolkit, v0.3. This is our biggest release yet, a... 阅读更多

三月 15, 20189

Introducing ML-Agents Toolkit v0.2: Curriculum Learning, new environments, and more

The Machine Learning team at Unity is happy to announce the release of a new version of Unity Machine Learning Agents Toolkit – v0.2 Beta! W... 阅读更多

十二月 8, 20179

Introducing: Unity Machine Learning Agents Toolkit

Our two previous blog entries implied that there is a role games can play in driving the development of Reinforcement Learning algorithms. A... 阅读更多

九月 19, 201772

Unity AI – Reinforcement Learning with Q-Learning

Welcome to the second entry in the Unity AI Blog series! For this post, I want to pick up where we left off last time, and talk about how to... 阅读更多

八月 22, 201715

Unity AI-themed Blog Entries

Who are these blog entries for? It is our objective to inform Unity Game Developers about the power of AI and ML approaches in game develop... 阅读更多

六月 26, 201722