Homeostasis Tissue-Like P Systems.

Area of Science:

• Theoretical Computer Science
• Computational Biology
• Formal Systems

Background:

• Tissue P systems are distributed parallel computing models inspired by biological cells and their environment.
• Existing models rely on environmental energy, creating a dependency that limits their autonomy.
• Biological homeostasis describes an organism's ability to maintain internal stability despite external changes.

Purpose of the Study:

• To introduce a novel computational model, homeostasis tissue-like P systems, by incorporating multiset rewriting rules and removing environmental energy dependency.
• To demonstrate the computational power and problem-solving capabilities of this new model.
• To establish a connection between computational systems and biological homeostasis.

Main Methods:

• Introduction of multiset rewriting rules into tissue P systems.
• Development of a computational model named homeostasis tissue-like P systems.
• Construction of uniform solutions for the 3-coloring problem and the SAT problem.

Main Results:

• Two uniform solutions were constructed in feasible time: one for 3-coloring in linear time and another for SAT in time-free mode.
• The constructed system can generate any Turing computable set of numbers.
• The system operates independently of the environment, mirroring biological homeostasis.

Conclusions:

• Homeostasis tissue-like P systems are a novel computational model that does not rely on environmental energy.
• These systems exhibit Turing universality and can effectively solve NP-complete problems, even in a time-free mode.
• The model successfully reflects the biological phenomenon of homeostasis in a computational context.