Elements of Game Theory in a Bio-inspired Model of Computation

Unconventional computing is a relatively recent research field in which new computation paradigms are studied, with emphasis on bio-inspired architectures and algorithms. The physical limitations of traditional systems make the exploration for new, alternative solutions a quest of great importance. In this direction, traditional and well-studied concepts are re-examined. In this paper, the connection between game theory, an established scientific field, and a bio-inspired model of computation based on P systems is studied. To this end, a novel bio-inspired game on a membrane system is introduced, in which the rules are inspired by fundamental mitochondrial processes. Furthermore, a general framework for connecting game-theoretic notions with a bio-inspired model of computation based on P systems is proposed. Finally, possibilities and further extensions that could shed light on the deeper connection among these fields are highlighted.

[1]  Theodore Andronikos,et al.  Mitochondrial fusion through membrane automata. , 2015, Advances in experimental medicine and biology.

[2]  M. Nowak,et al.  Evolutionary Dynamics of Biological Games , 2004, Science.

[3]  A. Grafen Biological signals as handicaps. , 1990, Journal of theoretical biology.

[4]  Theodore Andronikos,et al.  Membrane automata for modeling biomolecular processes , 2017, Natural Computing.

[5]  Georgios Ch. Sirakoulis,et al.  Hardware Acceleration of Cellular Automata Physarum polycephalum Model , 2015, Parallel Process. Lett..

[6]  Marian Gheorghe,et al.  Deterministic and stochastic P systems for modelling cellular processes , 2009, Natural Computing.

[7]  Yoshiharu Tanaka,et al.  Quantum-like dynamics of decision-making , 2012 .

[8]  Evgeny Katz,et al.  Biomolecular Computing Realized in Parallel Flow Systems: Enzyme-Based Double Feynman Logic Gate , 2015, Parallel Process. Lett..

[9]  Oscar H. Ibarra,et al.  On the Computational Complexity of P Automata , 2005, Natural Computing.

[10]  Peter Hammerstein,et al.  The second wave of evolutionary economics in biology. , 2005, Trends in ecology & evolution.

[11]  Gheorghe Paun,et al.  Languages and P Systems: Recent Developments , 2012, Comput. Sci. J. Moldova.

[12]  Paul G. Spirakis,et al.  The Contribution of Game Theory to Complex Systems , 2005, Panhellenic Conference on Informatics.

[13]  Theodore Andronikos,et al.  The mechanism of splitting mitochondria in terms of membrane automata , 2015, 2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT).

[14]  W. Hamilton,et al.  The evolution of cooperation. , 1984, Science.

[15]  D. Chan,et al.  Mitochondrial dynamics–fusion, fission, movement, and mitophagy–in neurodegenerative diseases , 2009, Human molecular genetics.

[16]  Theodore Andronikos,et al.  Particular Biomolecular Processes as Computing Paradigms. , 2020, Advances in experimental medicine and biology.

[17]  Michael Meyer-Hermann,et al.  Deceleration of Fusion–Fission Cycles Improves Mitochondrial Quality Control during Aging , 2012, PLoS Comput. Biol..

[18]  Steve B. Furber,et al.  Brain-inspired computing , 2016, IET Comput. Digit. Tech..

[19]  Athanasios V. Vasilakos,et al.  An overview of recent applications of Game Theory to bioinformatics , 2010, Inf. Sci..