Abstract: This paper aims at comparing the serial, shared memory parallelization, and distributed memory parallelization of the dynamic programming algorithm for the Knapsack Problem. Knapsack Problem ...

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 ...

Genomics is playing an important role in transforming healthcare. Genetic data, however, is being produced at a rate that far outpaces Moore’s Law. Many efforts have been made to accelerate genomics ...

ABSTRACT: Offline reinforcement learning (RL) focuses on learning policies using static datasets without further exploration. With the introduction of distributional reinforcement learning into ...

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 ...

Abstract: Dynamic programming is a fundamental algorithm that can be found in our daily lives easily. One of the dynamic programming algorithm implementations consists of solving the 0/1 knapsack ...

This is an implementation of the 0-1 knapsack problem in C using dynamic programming. The problem consists of a set of items, each with a weight and a value, and a knapsack with a maximum weight ...