Recently, gaming companies have become interested in using reinforcement learning and other machine learning techniques in game development.

An AI strategy proven adept at board games like Chess and Go, reinforcement learning, has now been adapted for a powerful protein design program. The results show that reinforcement learning can ...

Here we introduce an algorithm based solely on reinforcement learning, without human data, guidance or domain knowledge beyond game rules.

An MIT study finds reinforcement learning frustrates humans in teamplay — here's what that spells for this paradigm of ML in other areas.

As machines learn to play old Atari games like Space Invaders, Video Pinball, and Breakout, they're also learning to navigate the real world.

Deep Reinforcement Learning: An approach that integrates deep learning with reinforcement learning, enabling agents to process high-dimensional inputs and learn optimal actions in complex tasks.

In this paper we revise Reinforcement Learning and adaptiveness in Multi-Agent Systems from an Evolutionary Game Theoretic perspective. More precisely we show there is a triangular relation between ...

AI algorithms for deep-reinforcement learning have demonstrated the ability to learn at very high levels in constrained domains.

Reinforcement learning (RL) is a powerful type of AI technology that can learn strategies to optimally control large, complex systems.