Probabilistic Complexity Theory

#NPcompleteEqualsP#NPNotEqualscoNP and #PNotEqualscoP!!!

What is Non-deterministic is the Environment, and any NP problem can be P with the proper reduction of Uncertainty.

With a (Knowledge) map climbing any unknown mountain is #NPEqualsP.

Do you have the same probability of losing you than reaching the top with a (Knowledge) map? Of course not. #NPNotEqualscoNP

What’s the probability of losing you in an unknown mountain with a (Knowledge) map? Less than without a proper map.

Do you have the same probability of interpreting the map correctly and incorrectly? Of course not. #PNotEqualscoP

That opens a new discipline: “Deterministic Complexity in Uncertain and Non-deterministic Environments”

#ProbabilisticComplexityTheory #SocialRealityComplexity

Citing https://en.wikipedia.org/wiki/NP-completeness

“If any NP-complete problem has a polynomial time algorithm, all problems in NP do.”

Imagine then a route map with a Hamiltonian cycle over the mountain, following the route is #P even the real problem in the Environment is #NPcomplete so #NPcompleteEqualsP if properly dealt with.

https://en.wikipedia.org/wiki/Computational_complexity_theory

Shouldn’t we try to create the proper (Knowledge) maps to improve our Society? :

Author: Andrés García-Camino

Ph.D. in A.I.

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