Abstract: This study addresses a variant of the Vehicle Routing Problem (VRP) with customer priorities. In the variant, we assume the hard priority constraint where customers should be served in a ...

Explore the reinforcement learning algorithm that achieves performance comparable to GRPO in RLVR with minimal complexity. Learn how it works, why it’s effective, and its practical applications in RL ...

I recently read a book to my 4½-year-old daughter that I immediately took out of her room and decided never to read again. When I told Lila and Community Editor Elliot Steeves about the above column, ...

We publish the best academic work (that's too often lost to peer reviews & the TA's desk) to the global tech community ...

This project implements various reinforcement learning algorithms to play Spider Solitaire, a popular card game. The implementation includes DQN, A2C, and PPO algorithms with both full and simplified ...

In a groundbreaking development, engineers at Northwestern University have created a new AI algorithm that promises to transform the field of smart robotics. The algorithm, named Maximum Diffusion ...

Python is a general-purpose programming language and is one of the most popular languages because of its versatility, ease of use, libraries, and active community. Given its widespread adoption, it is ...

Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.

Diffusion models are a set of generative models that work by adding noise to the training data and then learn to recover the same by reversing the noising process. This process allows these models to ...