By leveraging inference-time scaling and a novel "reflection" mechanism, ALE-Agent solves the context-drift problems that ...

GPT-5.2 Pro delivers a Lean-verified proof of Erdős Problem 397, marking a shift from pattern-matching AI to autonomous ...

SuperQ Quantum Computing Inc. (CSE: QBTQ) (OTCQB: QBTQF) (FSE: 25X) ("SuperQ Quantum", "SuperQ", or the "Company"), a leader ...

Quantum computing is an emerging paradigm that leverages the principles of quantum mechanics to solve computational problems beyond the reach of classical computers. This article provides an overview ...

It remains an open question when a commercial quantum computer will emerge that can outperform classical (non-quantum) machines in speed and energy efficiency while solving real-world combinatorial ...

Abstract: Knowledge transfer-based evolutionary optimization has garnered significant attention, such as in multitask evolutionary optimization (MTEO), which aims to solve complex problems by ...

In the combinatorial semi-bandit (CSB) problem, a player selects an action from a combinatorial action set and observes feedback from the base arms included in the action. While CSB is widely ...

Scientists have built a physics-inspired computing system that uses oscillators, rather than digital processing, to solve complex optimization problems. Their prototype runs at room temperature and ...

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 ...

Introduction: Container relocation in port yards represents a canonical NP-hard problem, characterized by high-dimensional nonlinear constraints and stringent real-time decision-making requirements.