Agent observability, aka AgentOps, has emerged as a vital ecosystem of tools for keeping an eye on what AI agents and LLMs ...

A new quantum-inspired algorithm has cracked a problem so massive that conventional supercomputers struggle to even approach it. Researchers used the method to simulate extraordinarily complex quantum ...

Abstract: The energy storage self-scheduling (ESSS) problem is typically formulated as a mixed-integer linear programming (MILP) or quadratically constrained programming (QCP) model, reflecting the ...

A2Z/ ├── Problems/ # Solved problems organized by difficulty │ ├── Easy/ # Easy level problems │ ├── Medium/ # Medium level problems │ └── Hard/ # Hard level problems │ ├── DataStructures/ # Core data ...

Determining the least expensive path for a new subway line underneath a metropolis like New York City is a colossal planning challenge—involving thousands of potential routes through hundreds of city ...

Abstract: We present a simple performance bound for the greedy scheme in string optimization problems. Our approach generalizes the family of greedy curvature bounds established by Conforti and ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

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 ...

Machine learning holds the potential to solve many real-world problems, but interpretability is a necessary prerequisite for practitioners in high-stakes domains such as medicine and law. Decision ...