In computational complexity theory, P and NP are two classes of problems. P is the class of decision problems that a deterministic Turing machine can solve in polynomial time. In useful terms, any ...

Constraint satisfaction problems (CSPs) provide a versatile framework for modelling complex decision-making tasks where a collection of variables must be allocated values that satisfy specific ...

The historical pursuit of creating intelligent machines has culminated in the modern era of artificial intelligence. However, the efficacy of AI applications is contingent upon a nuanced understanding ...

NP-complete problems, including optimal routing, scheduling and network design, are foundational to essential tasks across various industries. However, they actually pose challenges for conventional ...

They have a mathematical, analog “solver” that can potentially find the best solution to NP-hard problems. NP-hardness is a theory of computational complexity, with problems that are famous for their ...