Many sequential decision problems can be formulated as Markov decision processes (MDPs) where the optimal value function (or cost-to-go function) can be shown to satisfy a monotone structure in some ...

Solution approaches developed to date have not been efficient enough to handle realistically sized problems. The main approaches have been general integer programming algorithms and the specialized ...

Probabilistic programming has emerged as a powerful paradigm that integrates uncertainty directly into computational models. By embedding probabilistic constructs into conventional programming ...

Programming Systems & Software Engineering research at Drexel University's College of Computing & Informatics (CCI) focuses on improving the design, construction, and maintenance of software systems, ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

Advanced study in models of computation, programming languages and algorithms with a specific focus on concurrent programming. The course includes models of computation, programming language paradigms ...

Mathematical Background: We expect that the student is comfortable with basic mathematics at the level of a U.S. first-year college STEM student. This includes basic notions such as sets and functions ...

Computers can be used to help solve problems. However, before a problem can be tackled, it must first be understood. Computational thinking helps us to solve problems. Designing, creating and refining ...

CBSE Class 12 Maths Mind Map Linear Programming: The Central Board of Secondary Education (CBSE) is a popular school board in India and conducts the year-end board exams for lakhs of students. It’s ...