The paper solves the stochastic inverse optimal problem. Dynamic programming is used to transform the original problem into a differential equation. Such an equation is well-defined (with probability ...

Significant advances in programming have been made over the last thirty years, with technologies such as structured programming, object-oriented programming, Booch object-oriented design, etc. Even ...

It also fits into the formal paradigm presented in goal programming. In goal programming, the objective functions typically take on the role of driving a linear function of the structural variables to ...

Niv Buchbinder, Kamal Jain, Mohit Singh, Secretary Problems via Linear Programming, Mathematics of Operations Research, Vol. 39, No. 1 (February 2014), pp. 190-206 ...

In this article, author Markus Völter discusses the future of programming using Large Language Model (LLM) tools like ChatGPT and GitHub’s Copilot for prose-to-code generation. He also talks ...

Marshall, Paul W. "Linear Programming: A Technique for Analyzing Resource Allocation Problems." Harvard Business School Background Note 171-322, January 1971. (Revised November 1975 ...

Yet, while coding as we know it is indeed facing disruption, the creative, problem-solving essence of computer programming is likely to remain a largely human endeavor for the foreseeable future.

The Rust project wants more developers to use the programming language but admits it has a challenge with adoption.

The artificial intelligence start-up said the new system, OpenAI o3, outperformed leading A.I. technologies on tests that rate skills in math, science, coding and logic.

The subject will be pitched at those seeking a “demanding cognitive level” and focus on a new approach to solving real-world problems.