Biological Computation as the Revolution of Complex Engineered Systems

TL;DR

This paper argues that biological computation, which operates beyond traditional Turing limits, can revolutionize the engineering of complex systems by providing a new theoretical framework based on hypercomputation.

Contribution

It introduces the concept that biological computation requires a shift from classical to hypercomputational models for complex engineered systems.

Findings

Biological systems perform hypercomputation.

Current science views biological processing as intractable.

A new computational theory beyond Turing is needed.

Abstract

Provided that there is no theoretical frame for complex engineered systems (CES) as yet, this paper claims that bio-inspired engineering can help provide such a frame. Within CES bio-inspired systems play a key role. The disclosure from bio-inspired systems and biological computation has not been sufficiently worked out, however. Biological computation is to be taken as the processing of information by living systems that is carried out in polynomial time, i.e., efficiently; such processing however is grasped by current science and research as an intractable problem (for instance, the protein folding problem). A remark is needed here: P versus NP problems should be well defined and delimited but biological computation problems are not. The shift from conventional engineering to bio-inspired engineering needs bring the subject (or problem) of computability to a new level. Within the frame of computation, so far, the prevailing paradigm is still the Turing-Church thesis. In other words, conventional engineering is still ruled by the Church-Turing thesis (CTt). However, CES is ruled by CTt, too. Contrarily to the above, we shall argue here that biological computation demands a more careful thinking that leads us towards hypercomputation. Bio-inspired engineering and CES thereafter, must turn its regard toward biological computation. Thus, biological computation can and should be taken as the ground for engineering complex non-linear systems. Biological systems do compute in terms of hypercomputation, indeed. If so, then the focus is not algorithmic or computational complexity but computation-beyond-the-Church-Turing-barrier. We claim that we need a new computational theory that encompasses biological processes wherein the Turing-Church thesis is but a particular case.