ICMC 2021 - International Conference on Membrane Computing

Bogdan Aman: Evolution strategies in membrane computing

Abstract: Membrane systems consist of a set of rewriting rules over (multi)sets of objects, together with an initial (multi)set of objects; membrane systems are used to describe the dynamics of systems which involve parallel access to resources. The evolution of a membrane system consists of applying rules over available resources (objects) using various strategies. We give a survey of the computation power and efficiency of membrane systems using various evolution strategies.

Bogdan Aman graduated the Alexandru Ioan Cuza University of Iasi (Faculty of Mathematics) in 2007 and completed his Ph.D. thesis in 2009 under the supervision of Prof. Gabriel Ciobanu at the Romanian Academy (Iasi branch). He received a public recognition for his research with the 2013 Grigore Moisil Award of the Romanian Academy of Sciences and 2019 International Membrane Computer Society (IMCS) Prize for the Theoretical Result of the Year. His main research fields are membrane computing, natural computing, process algebra, type systems, and other theoretical aspects of computer science.

Mario J. Pérez Jiménez: Membrane systems breaking cryptosystems

Abstract: Cryptography is a scientific discipline that concerns information security in presence of possible intruders, as well as authentication and identification, providing privacy and integrity. The first ever published public key cryptosystem, named RSA, was developed by R. Rivest, A. Shamir and L. Adleman in 1978. The security that resides in this system is based on the apparent computational hardness of the integer factorization problem. More precisely, the semiprime factorization problem (given a natural number product of two prime numbers, find its decomposition) is used. In this talk, the cited problem, among others, is studied from the Membrane Computing perspective, and a new kind of membrane systems with the ability to compute partial functions among natural numbers, are presented. This provides a new approach to attack RSA cryptosystems.

Mario J. Pérez Jiménez is full Professor at the Department of Computer Science and Artificial Intelligence at Universidad de Sevilla, Spain, since 2009, and currently Emeritus Professor. From 2005 to 2007 he was a Guest Professor of the Huazhong University of Science and Technology, Wuhan, China. He is a numerary member of the Academia Europaea (The Academy of Europe) in the Section of Informatics. His main research interests include theory of computation, computational complexity theory, natural computing (DNA computing and membrane computing), bioinformatics and computational modelling for complex systems. He has published 19 books in computer science and mathematics, and over 300 scientific papers in international journals (collaborating with researchers worldwide) and he is a member of the Editorial Board of six ISI journals. He has been the first scientist awarded with “Important Contributions to Membrane Computing” under the auspices of the European Molecular Computing Consortium, Edinburgh, 2008. In 2014, he received the University of Sevilla’s FAMA award for his outstanding research career. He has been the main researcher in various European, Asian, Spanish and Andalusian research grants. From 2003 he is an expert reviewer of the Prospective and Evaluation National Agency of Spain. From May 2006 he is an European Science Foundation peer reviewer, from July 2008 he is an expert reviewer from the Romanian National University Research Council and from October 2015 he is an international expert from the Russian Science Foundation, invited by the Russian International Affairs Council.

Petr Sosík: Simulations of bacteria with morphogenetic systems

Abstract: (Joint work with Martin Pavlíček) Morphogenetic (M) systems is a computational model inspired by morphogenesis of living cells. Mathematically, it is based partly on the concept of P systems with proteins on membranes providing abstract metabolic processes, and partly on the algorithmic self-assembly of tiles. An M system, however, generalizes both concepts into a unique framework. It allows to self- assemble 1D or 2D primitives of arbitrary pre-defined shapes into 2D or 3D forms, while the process is controlled by flow of atomic objects due to P-system-like rules. It was shown that M systems are computationally universal, error-prone, with strong self-healing properties, and able to solve NP- hard problems in a polynomial time. Here we show that M systems are also able to simulate key processes in bacteria on a high level of granularity, while following important qualitative and quantitative macro-properties of the simulated cells. Initial experiments simulating growth of cytoskeleton inside cells were extended to cell fission processes under changing environmental conditions and to resistance of cells (e.g., E.Coli) to antibiotic agents. We show that, in spite of relative simplicity of the designed models of both prokaryotic and eukaryotic cells, their results faithfully correspond to published biological observations.

Petr Sosík is is a professor at the Department of Computer Science, School of Philosophy and Science, Silesian University, Opava. He is a head of research unit and a guarantee of several study programs. His research covers the area of bio-inspired computing (DNA computing, membrane computing, morphogenetic systems) and lately also machine learning applications. He has (co-)authored over 100 book chapters, journal and refereed conference publications. He supervises the work of several PhD students. Several times he was awarded the Best Paper Award or Research Result of the Year.

Sergey Verlan: A formal look at spiking neural P systems

Abstract: In this talk we will consider the model of spiking neural P systems (SNP) from the formal perspective. Based on the formal framework for P systems we decompose the model and its semantics in distinct bricks and then show how different existing variants of SNP can be constructed from them. This allows to compare different variants of SNP systems, to extend them and to provide bisimulations. We will also discuss the vector notation for the description of SNP systems and the relations (bisimulations) to other variants of P systems and related models (like Petri nets).

Sergey Verlan is a full professor at the Department of Computer Science, School of Science and Technology, University of Paris, France. He received his PhD in Computer Science at the University of Metz, France (2004). He obtained a habilitation in Computer Science (2010). Currently he is an associated professor (maître de conferences) at the University of Paris Est Créteil (France). His research interests belong to the area of theoretical computer science and natural computing. He has expertise in the area of formal language theory, DNA computing, membrane computing, modeling of biological systems and hardware design. He is particularly interested in the universality problem and provided several universal constructions which are the smallest known for the corresponding classes. He also introduced the formal framework for P systems that allows to explain, compare and extend different variants of P systems.He has more than 100 articles published in scientific journals and international conference proceedings. He edited 6 special journal issues and contributed to 12 book chapters.