Abstract: Deep reinforcement learning (RL) typically requires a tremendous number of training samples, which are not practical in many applications. State abstraction and world models are two ...

Flexion's Reflect v1.0 enables humanoid robots to complete complex multi-step tasks, raising mission success from 38 percet ...

Second Reality is a legendary demoscene release by Future Crew, which won Assembly 1993 with its technical and artistic ...

Open-source agentic coding model Ornith-1.0, released today under the MIT license, uses a self-improving reinforcement ...

Robots with increasingly precise dexterity are becoming essential in everyday life and industrial settings, from assembling tiny smartphone components to assisting doctors in surgery. However, ...

Matt Fitzpatrick, CEO of Invisible Technologies talk about the use of reinforcement learning by frontier model providers for training and the company's enterprise business. From reinforcement learning ...

Abstract: Network slicing-based communication systems can dynamically and efficiently allocate resources for diversified services. However, due to the limitation of the network interface on channel ...

EMBED <iframe src="https://archive.org/embed/pc-gamer-demo-disc-collection" width="560" height="384" frameborder="0" webkitallowfullscreen="true" mozallowfullscreen ...

Adrian has been writing, critiquing, and thinking about games since he first picked up an N64 controller many years ago. These days he writes reviews, news, and features for Game Rant and believes ...

A delivery agent trained with reinforcement learning to optimize courier routing on real street maps, accounting for dynamic traffic, package priorities, and delivery deadlines, with a live ...