Abstract: Deep Reinforcement Learning (DRL) has gained significant attention for its ability to solve combinatorial optimization problems, including the Traveling Salesman Problem (TSP). While ...

In terms of the agents you build, Bayer put up its own agent system on Foundry, and now it has 20,000 of its own employees on it.

In mid-May, OpenAI announced that an internal AI model had disproved the Erdős unit distance conjecture, a famous problem in discrete geometry that had stumped human mathematicians for the last 80 ...

A general-purpose Model Context Protocol (MCP) server for solving combinatorial optimization problems with logical and numerical constraints. This server provides a unified interface to multiple ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

Abstract: Plenty of decision variable grouping-based algorithms have shown satisfactory performance in solving high-dimensional optimization problems. However, most of them are tailored for ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

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The rise of AI, graphic processing, combinatorial optimization and other data-intensive applications has resulted in data-processing bottlenecks, as ever greater amounts of data must be shuttled back ...

The paper presents a topology optimization methodology for 2D elastodynamic problems using the boundary element method (BEM). The topological derivative is derived based on the variation method and ...