The takeaway leadership message from our May issue is clear: Future progress will come from those willing to rethink the machinery — not just the medicine. If there’s a common thread running through ...

Discover how predictive analytics uses data-driven models like decision trees and neural networks to forecast outcomes and ...

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 ...

Abstract: With advancements in technology, commercial aircraft formation flying is becoming increasingly feasible as an efficient and environmentally friendly flight method. However, gaps remain in ...

Linear Programs (LPs) are one of the major building blocks of AI and have championed recent strides in differentiable optimizers for learning systems. While efficient solvers exist for even ...

Forbes contributors publish independent expert analyses and insights. Caroline Castrillon covers career, entrepreneurship and women at work. Non-linear careers represent a fundamental shift in how we ...

This paper deals with linear programming techniques and their application in optimizing lecture rooms in an institution. This linear programming formulated based on the available secondary data ...

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 ...

The cerebral cortex is strongly recurrently connected with complex wiring rules. This circuitry can now be probed by studying responses to optogenetic perturbations of one or small numbers of cells.