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 ...

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 ...

A critical factor in the success of many decision support systems is the accurate modeling of user preferences. Psychology research has demonstrated that users often develop their preferences during ...

A proposal is made for including in a programming language statements which imply relations between variables but which are not explicit assignment statements. The compiler sets up a Newtonian ...

Mathematical programming with vanishing constraints (MPVC) represents a challenging class of optimisation problems where certain constraints become inactive—or “vanish”—depending on specific ...

Functional programming, as the name implies, is about functions. While functions are part of just about every programming paradigm, including JavaScript, a functional programmer has unique ...

Integer Linear Programming (ILP) is the foundation of combinatorial optimization, which is extensively applied across numerous industries to resolve challenging decision-making issues. Under a set of ...

AI constraint solver in Java to optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems. The open source ...

Since the open-pit precedence-constrained production scheduling problem is an NP-hard problem, solving it is always a challenging task, especially from a long-term perspective because a mineral ...