Probabilistic programming has emerged as a powerful paradigm that integrates uncertainty directly into computational models. By embedding probabilistic constructs into conventional programming ...

Primal methods constitute a common approach to solving (combinatorial) optimization problems. Starting from a given feasible solution, they successively produce new feasible solutions with ...

In this Artificial Intelligence podcast with Lex Fridman, computer scientist Donald Knuth discusses Alan Turing, Neural networks, machine learning and other AI topics from ant colonies and human ...

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Getting to the heart of causality is central to understanding the world around us. What causes one variable—be it a biological species, a voting region, a company stock, or a local climate—to shift ...

This paper presents a constraint logic programming model for the traveling salesman problem with time windows which yields an exact branch-and-bound optimization algorithm without any restrictive ...

The human brain is the most sophisticated organ in the human body. The things that the brain can do, and how it does them, have even inspired a model of artificial intelligence (AI). Now, a recent ...