scholarly journals Technology Self-organizing Ensembles of Intelligent Agents with Collective Synergetic Interaction

2020 ◽  
Vol 8 (4) ◽  
pp. 29
Author(s):  
Evgeny Bryndin
Keyword(s):  
Intelligent Agents ◽  
Self Organizing

Instrumental Means for Managing the Rational Behavior of Self-Organizing Autonomous Intelligent Agents

2021 ◽  
Vol 22 (4) ◽  
pp. 171-180
Author(s):  
V. B. Melekhin ◽  
M. V. Khachumov
Keyword(s):  
Intelligent Agents ◽  
Environmental Changes ◽  
A Priori ◽  
Operating Conditions ◽  
Basic Principles ◽  
Purposeful Behavior ◽  
Problem Solvers ◽  
Boundary Estimates ◽  
Self Learning ◽  
Self Organizing

We formulate the basic principles of constructing a sign-signal control for the expedient behavior of autonomous intelligent agents in a priori undescribed conditions of a problematic environment. We clarify the concept of a self-organizing autonomous intelligent agent as a system capable of automatic goal-setting when a certain type of conditional and unconditional signal — signs appears in a problem environment. The procedures for planning the expedient behavior of autonomous intelligent agents have been developed, that imitate trial actions under uncertainty in the process of studying the regularities of transforming situations in a problem environment, which allows avoiding environmental changes in the process of self-learning that are not related to the achievement of a given goal. Boundary estimates of the proposed procedures complexity for planning expedient behavior are determined, confirming the possibility of their effective implementation on the on-board computer of the automatic control system for the expedient activity of autonomous intelligent agents. We carry out an imitation on a personal computer of the proposed procedures for planning purposeful behavior, confirming the effectiveness of their use to build intelligent problem solvers for autonomous intelligent agents in order to endow them with the ability to adapt to a priori undescribed operating conditions. The main types of connections between various conditional and unconditional signal — signs of a problem environment are structured, which allows autonomous intelligent agents to adapt to complex a priori undescribed and unstable conditions of functioning.

scholarly journals Crowd intelligence evolution based on complex network

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jianran Liu ◽  
Wen Ji
Keyword(s):  
Complex Network ◽  
Intelligent Agents ◽  
Cooperative Behavior ◽  
Content Type ◽  
Interactive Behavior ◽  
Interactive Network ◽  
Interactive Relationship ◽  
Evolution Behavior ◽  
Crowd Intelligence ◽  
Self Organizing

Purpose In recent years, with the increase in computing power, artificial intelligence can gradually be regarded as intelligent agents and interact with humans, this interactive network has become increasingly complex. Therefore, it is necessary to model and analyze this complex interactive network. This paper aims to model and demonstrate the evolution of crowd intelligence using visual complex networks. Design/methodology/approach This paper uses the complex network to model and observe the collaborative evolution behavior and self-organizing system of crowd intelligence. Findings The authors use the complex network to construct the cooperative behavior and self-organizing system in crowd intelligence. Determine the evolution mode of the node by constructing the interactive relationship between nodes and observe the global evolution state through the force layout. Practical implications The simulation results show that the state evolution map can effectively simulate the distribution, interaction and evolution of crowd intelligence through force layout and the intelligent agents’ link mode the authors proposed. Originality/value Based on the complex network, this paper constructs the interactive behavior and organization system in crowd intelligence and visualizes the evolution process.

Review of Pattern Recognition by Self-Organizing Neural Networks.

1995 ◽  
Vol 40 (11) ◽  
pp. 1110-1110
Author(s):  
Stephen James Thomas
Keyword(s):  
Neural Networks ◽  
Pattern Recognition ◽  
Self Organizing

Modeling student knowledge with self-organizing feature maps.

1993 ◽  
Author(s):  
Steven A. Harp ◽  
Tariq Samad ◽  
Michael Villano
Keyword(s):  
Feature Maps ◽  
Student Knowledge ◽  
Self Organizing

Understanding Change in Self-Organizing Systems: a Systemic View

2012 ◽  
Author(s):  
Markus Schwaninger ◽  
Stefan Groesser
Keyword(s):  
Systemic View ◽  
Self Organizing

Art as a Self-Organizing Complex System

1998 ◽  
Author(s):  
Svetlana Apenova ◽  
Igor Yevin
Keyword(s):  
Complex System ◽  
Self Organizing

Gestalt Self-Organizing Forces in Visual Memory

1992 ◽  
Author(s):  
Lewis O. Harvey ◽  
Anne Igel ◽  
Eric K. Schmidt
Keyword(s):  
Visual Memory ◽  
Self Organizing

Towards Self-Organizing Economy

2006 ◽  
Author(s):  
Elena Pugacheva ◽  
Konstantin Solovienko
Keyword(s):  
Self Organizing

Application of Fractal Methods to Ensure the Cyber-Resilience of Self-Organizing Networks

2019 ◽  
Vol 22 (4) ◽  
pp. 336-341
Author(s):  
D. V. Ivanov ◽  
D. A. Moskvin
Keyword(s):  
Information Security ◽  
Network Structure ◽  
Self Regulation ◽  
Security Threats ◽  
Self Organizing Networks ◽  
Self Organizing ◽  
Fractal Methods

In the article the approach and methods of ensuring the security of VANET-networks based on automated counteraction to information security threats through self-regulation of the network structure using the theory of fractal graphs is provided.

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