Learn how to solve problems using linear programming. A linear programming problem involves finding the maximum or minimum value of an equation, called the objective functions, subject to a system of ...
In the era of A.I. agents, many Silicon Valley programmers are now barely programming. Instead, what they’re doing is deeply, ...
In another forum, a poster pointed out that AIs are tweaked, even before release, to reduce errors and inappropriate results. AIs are constrained-guessing devices. Ordinary language rules for ...
Oracle-based quantum algorithms cannot use deep loops because quantum states exist only as mathematical amplitudes in Hilbert space with no physical substrate. Criticall ...
Abstract: This letter addresses distributed nonconvex constrained optimization problems, where both the local cost function and the inequality constraint function are nonconvex. Firstly, the global ...
Abstract: This paper proposes a hybrid mixed-integer quadratic programming-constrained deep reinforcement learning (MIQP-CDRL) framework for energy management of multi-energy communities. The ...
You can set up the environment using the environment.yml (the requirement is the same as [DDRM]: https://github.com/bahjat-kawar/ddrm). Run conda env create -f ...
Note: Most of my prior work has been in internal systems/data environments. This is a small public prototype to demonstrate my modeling approach and decision-support packaging. A small, reproducible ...
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