The rise of AI-driven automation is no longer a future trend—it’s already reshaping how individuals and institutions trade ...

Abstract: In scenarios where multiple decision-makers operate within a common decision space, each focusing on their own multi-objective optimization problem (e.g., bargaining games), the problem can ...

Alibaba's HDPO framework trains AI agents to skip unnecessary tool calls, cutting redundant invocations from 98% to 2% while ...

Explaining search visibility to stakeholders used to be as simple as pointing to a number one ranking. Now, as search ...

Researchers at EPFL have developed 'Synthegy', a framework that uses large language models to evaluate and guide chemical synthesis planning and reaction mechanism analysis through natural-language ...

New research and industry developments show AI is transforming structural engineering through specialized tools that optimize ...

This research introduces a VSLAM framework that optimizes obstacle avoidance in indoor logistics, leveraging advanced ...

Foundational optimization algorithms are the core driving force behind deep learning, evolving from early stochastic gradient descent (SGD) to the widely adopted Adam family. However, as the scale of ...

Abstract: Large-scale multi-objective optimization problems (LSMOPs) pose challenges to existing optimizers since a set of well-converged and diverse solutions should be found in huge search spaces.