Substantive agency characterization links key complexity classes conditionally
Substantive Agency and Computational Non-Anticipability: An Axiomatic Route to a Conditional Separation of P and N P
Summary
This paper explores a formal way to describe decision-making called substantive agency and connects it to a major question in computer science about whether all problems whose solutions can be checked quickly can also be solved quickly (the P vs NP problem). The authors show that under specific conditions involving how decisions can be chosen or predicted, this leads to an important conclusion about P and NP being equal. However, their result depends on assumptions and does not prove that human decisions meet these criteria. Instead, it provides a conditional theoretical bridge between concepts in agency and computational complexity.
What this means in practice
- •For complexity theorists: Clarify conditional relations between complexity classes P and NP under agency assumptions, refining theoretical understanding.
- •For algorithm designers: Assess algorithm feasibility with respect to decision-making models linked to substantive agency constraints and polynomial-time selectors.
A theory result. No direct application yet.