Reinforcement learning and simulation are essential to solving the constraints and novel challenges that take place in factories and supply chains. TechCrunch Desktop Logo TechCrunch Mobile Logo.

In this project, we aim at using deep reinforcement learning techniques to improve the scheduling of radio resources in advanced cellular networks (LTE/5G). OpenAI Gym, NS-3 and NS-3 gym will be used: ...

Inside a simple computer simulation, a group of self-driving cars are performing a crazy-looking maneuver on a four-lane virtual highway. ... Reinforcement Learning. Breakthrough ...

Deep reinforcement learning has trained AIs to beat humans at complex games like Go and StarCraft. Could it also do a better job at running the economy? Income inequality is one of the overarching ...

About a dozen members of the Google Brain team today open-sourced Google Research Football Environment, a 3D reinforcement learning simulator for training AI to master soccer.

In all, reinforcement learning suffers from the same limitations as regular machine learning. It’s an ideal option for domains that are evolving and where some data is unavailable at the start.

GPU-based physics simulator speeds up reality by “1,000x” while GPT-4 calls the shots. ... Eureka introduces a novel form of reinforcement learning from human feedback ...

This study seeks to construct a basic reinforcement learning-based AI-macroeconomic simulator. We use a deep RL (DRL) approach (DDPG) in an RBC macroeconomic model. We set up two learning scenarios, ...