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• EVOLUTIONARY DESIGN AS A TOOL FOR DEVELOPING MULTI-AGENT SYSTEMS

  L.A. Gladkov , N.V. Gladkova

  2020-11-22

  Abstract ▼

  The article is devoted to the discussion of the problems of constructing evolving multi-agent systems
  based on the use of the principles of evolutionary design and hybrid models. The concept of an
  agent is considered. A set of basic properties of the agent is presented. The analogies between multiagent
  and evolutionary systems are considered. The principles of construction and organization of multi-
  agent systems are considered. The similarities between the main definitions of the theory of agents
  and the theory of evolution are noted. It that the main evolution models and evolutionary algorithms can
  be successfully used in the design of multi-agent systems is noted. The analysis of existing methods andmethodologies for designing agents and multi-agent systems is carried out. The existing differences in
  approaches to the design of multi-agent systems are noted. The main types of models are described and
  their most important characteristics are given. A model of agent interaction, including a description of
  services (services), relationships and obligations existing between agents is presented. The model of
  relations (contacts), which defines communication links between agents is described. The importance
  and prospects of using the agent-based approach to the design of multi-agent systems are noted. The
  concept of designing agents and multi-agent systems, according to which the design process includes the
  basic components of self-organization, including the processes of interaction, crossing, adaptation to the
  environment, etc is proposed. Various approaches to the evolutionary design of artificial systems are
  considered. An evolutionary model of the formation of agents and agencies as the main component of
  evolutionary design is proposed. Modified evolutionary crossing-over operators to implement the agent
  design process are proposed.

• EVOLUTIONARY DESIGN AS A TOOL FOR DEVELOPING MULTI-AGENT SYSTEMS

  L. A. Gladkov, N. V. Gladkova

  2021-11-14

  Abstract ▼

  The article is devoted to the discussion of the problems of constructing evolving multi -
  agent systems. Possible methodologies for designing multi-agent systems are considered. The
  relevance of developing new principles for constructing multi -agent systems based on evolutionary
  design methods is noted. The correspondences between the terms of the theory of
  agents and the theory of evolution are highlighted. The prospects of using hybrid approaches
  to the design of multi-agent systems are noted. The principles of construction and the poss ibility
  of using fuzzy genetic algorithms in the design of multi -agent systems are considered.
  It is suggested that the models and methods of the theory of evolutionary modeling can be
  successfully applied in the design of multi-agent systems. An evolving multi-agent system is
  proposed. The procedure for the formation of new agents in the process of evolution is described.
  The set of parameters for assessing the state of each agent in the population has
  been determined. The resource parameters are proposed to be used to assess the current state
  of the agent and the possibilities of its interaction with other agents. The definitions of an
  agency and a family, the minimum elements of an evolving multi -agent system are given. An
  evolutionary strategy for constructing a model of an evolving multi -agent system is proposed.
  The procedures for the execution of the original evolutionary operators for processing the
  population of agents are described. Based on the proposed methodology, a software system
  for supporting the evolutionary design of agents and multi-agent systems was developed. Atpresent, computational experiments are being carried out to study the proposed design model
  for multi-agent systems, as well as to evaluate the effectiveness of various operators and
  schemes for the formation of descendant agents, the necessary conditions for survival.

• HYBRID APPROACH THE JOINT SOLUTION OF PLACEMENT AND TRACING PROBLEMS

  L.A. Gladkov , N. V. Gladkova , Dzhabbar Yasir Yasir Mukhanad

  2020-11-22

  Abstract ▼

  The article proposes an integrated approach to solving the problems of placing and tracing elements
  of circuits of electronic computing equipment. The approach is based on the joint solution of
  placement and tracing problems using fuzzy genetic methods. A description of the problem under
  consideration is given and a brief analysis of existing approaches to its solution is performed. The
  article discusses integrated approaches to solving optimization problems of computer-aided design of
  digital electronic computing equipment circuits. The urgency and importance of developing new
  effective methods for solving such problems is emphasized. It is noted that an important direction in
  the development of optimization methods is the development of hybrid methods and approaches that
  combine the advantages of various methods of computational intelligence. The article describes the
  following main points: the structure of the proposed algorithm and its main stages; modified genetic
  crossover operators; models for the formation of the current population are proposed; modified heuristics,
  operators and strategies for finding optimal solutions. The results of computational experiments
  are presented. The experiments carried out confirm the effectiveness of the proposed approach.
  In conclusion, a brief analysis of the results obtained is given.

• METAHEURISTIC OPTIMIZATION METHOD BASED ON THE STEM CELL BEHAVIOR MODEL

  Y. V. Danilchenko , V.I. Danilchenko, V.M. Kureichik

  2022-05-26

  Abstract ▼

  The paper discusses optimization methods that are based on processes occurring in nature. Such
  methods have become increasingly used to solve complex problems. However, such methods have some
  drawbacks, which stimulates the development of new and more advanced optimization methods. Solving
  NP complete problems requires optimal methods that will meet all design requirements, so there is a
  need to develop new and more advanced methods for solving this class of problems. As such a method,
  the authors propose an optimization method based on a model of the behavior of stem cells in the natural
  environment. The conducted studies of the proposed method provide solutions that can overcome
  many of the shortcomings of standard optimization approaches, such as getting into the local optimum
  or low convergence rate of the algorithm based on the method under consideration. The purpose of this
  work is to develop an optimization method and an algorithm based on it for solving a complex objective
  function. The scientific novelty lies in the development of an optimization method based on the stem cell
  behavior model for solving NP complete problems. The aim of the work is to create conditions for theoptimal search for a solution to complex functions by applying the search method and, based on it, an
  algorithm for the behavior of stem cells. The practical value of the work lies in the development of a new
  metaheuristic optimization method for the efficient solution of NP complete problems. Also in the work,
  a comparative analysis with well-known competitors was carried out. The main difference of the proposed
  method from other known methods is the use of a new approach of bioinspired search based on
  the behavior of stem cells, which, as shown by practical comparison, has an advantage over known
  analogues. The results of a practical comparison of methods and algorithms based on them showed the
  advantages of the approach proposed in the work on known test functions. After analyzing the problem
  of creating methods, algorithms and software for solving NP complete problems, we can conclude that
  the development of such approaches is currently an urgent task.