Abstract: In this article, we investigate the optimal control problem for an unknown linear time-invariant system. To solve this problem, a novel composite policy iteration algorithm based on adaptive ...

Adaptive optimal control in dynamic systems merges the principles of adaptation and optimality to regulate systems whose behaviour or environment evolve over time. At its core, this field addresses ...

Dynamic object detection and segmentation in three-dimensional environments is a multidisciplinary field at the intersection of computer vision, robotics and remote sensing. The core challenge lies in ...

In the era of A.I. agents, many Silicon Valley programmers are now barely programming. Instead, what they’re doing is deeply, deeply weird. Credit...Illustration by Pablo Delcan and Danielle Del Plato ...

RGB-Thermal semantic segmentation employs complementary visual information of both RGB and thermal images to predict pixel-level label maps. How to learn their complementary features and fuse them ...

This study develops a unified framework for optimal portfolio selection in jump–uncertain stochastic markets, contributing both theoretical foundations and computational insights. We establish the ...

Cell segmentation is a crucial step in numerous biomedical imaging endeavors—so much so that the community is flooded with publicly available, state-of-the-art segmentation techniques ready for out-of ...

This project implements a Dynamic Programming (DP) solution for optimal inventory control, inspired by fundamental principles in Dimitri Bertsekas's work on "Lessons from AlphaZero for Optimal, Model ...

Most B2C marketers think they already know everything about customer segmentation. You create a list of similar buyers, send them a targeted email, and it drives better conversion rates because it’s ...

Abstract: Segmentation of handwritten input into individual characters is a crucial step in many connected handwriting recognition systems. This paper describes a segmentation algorithm for letters in ...