FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.

Deep neural networks (DNNs) have become a cornerstone of modern AI technology, driving a thriving field of research in ...

Asking someone, "What's your problem?" can seem like a confrontational challenge. It's like saying, "So, tell me: What's irking you? What is it that's nagging you or getting under your skin, ...

Master techniques for advisors to address financial constraints with clients, covering risk management, tax, and regulatory issues while building trust and crafting effective plans.

Abstract: Solving constrained multiobjective optimization problems (CMOPs) is a highly challenging work. Numerous complex nonlinear constraints significantly add to the complexity of CMOPs, resulting ...

Abstract: The finite resources of automated guided vehicles (AGVs) and machines in a flexible manufacturing system necessitate the integrated scheduling of production and transportation tasks to ...

India stands at a pivotal moment in its journey towards universal health coverage—a crucial component of the government's Viksit Bharat vision to elevate it to the status of a developed country by ...

ABSTRACT: This paper introduces a methodology that enables the relational learning framework to incorporate quantitative data derived from experimental studies in microbial ecology. The focus of using ...

This repository contains a JAX implementation of Πnet, an output layer for neural networks that ensures the satisfaction of specified convex constraints. TL;DR: Πnet leverages operator splitting for ...

This repository implements Physics-Informed Neural Networks (PINNs) for power grid analysis and renewable energy applications. The project combines deep learning with physical constraints to solve ...