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

Fuzzy optimisation has emerged as a vital framework for addressing decision-making and extremum problems where data ambiguity and uncertainty preclude the direct application of classical optimisation ...

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 ...

We might be witnessing the start of a new computing era where AI, cloud and quantum begin to converge in ways that redefine ...

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 ...

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 ...

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 ...

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.

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 ...