Abstract: This study proposes LiP-LLM: integrating linear programming and dependency graph with large language models (LLMs) for multi-robot task planning. For multi-robots to efficiently perform ...

Are you looking to enhance your skills and explore new career opportunities in Artificial Intelligence? In a world where technology is transforming every industry, Artificial Intelligence (AI) skills ...

Programming-by-Examples (PBE) involves synthesizing an intended program from a small set of user-provided input-output examples. A key PBE strategy has been to restrict the search to a carefully ...

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In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

Abstract: As one of the most critical components in modern LP solvers, presolve in linear programming (LP) employs a rich set of presolvers to remove different types of redundancy in input problems by ...

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the basis or foundation in machine learning. In this video, we will learn what is ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. There is a need for design strategies that can support rapid and widespread deployment ...

I’m not a programmer. But I’ve been creating my own software tools with help from artificial intelligence. Credit...Photo Illustration by Ben Denzer; Source Photographs by Sue Bernstein and Paul ...

Mixed Integer Linear Programming (MILP) is essential for modeling complex decision-making problems but faces challenges in computational tractability and requires expert formulation. Current deep ...