By leveraging inference-time scaling and a novel "reflection" mechanism, ALE-Agent solves the context-drift problems that ...
Bilevel optimisation represents a class of hierarchical decision-making processes where two interrelated optimisation problems are solved sequentially. In such problems, the upper-level (or leader) ...
Combinatorial optimisation is a fundamental field in applied mathematics and computer science that focuses on finding an optimal object from a finite set of objects. In this context, problems are ...
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 ...
BOZEMAN, Mont.--(BUSINESS WIRE)--FICO (NYSE: FICO): Global analytics software leader FICO today announced that the 2024 FICO® Xpress Best Paper Award went to a team that developed an algorithm for ...
A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...
We might be witnessing the start of a new computing era where AI, cloud and quantum begin to converge in ways that redefine ...
Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...
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Q&A: How AI could optimize the power grid
Artificial intelligence has captured headlines recently for its rapidly growing energy demands, and particularly the surging ...
The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...
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