Recognizing Team Formations in Multiagent Systems: Applications in Robotic Soccer

Coordination of the multi agent system and ITS application to robot soccer

Strategies and prediction in multi-agent systems

Piping system response induced by thermal-hydraulic transient: A review of recent analysis methods and experiments

The research focuses on methods and software tools for decision support for the organization of distributed production of unmanned aerial vehicles (UAVs) based on digital twin and multi-agent systems technologies. The purpose of the work is to provide a critical review of existing approaches to the organization of distributed production of UAVs, as complex technical objects, and to substantiate an approach to building a multi-agent decision support system for the synthesis of a rational production structure based on digital twins of participants in production cooperation. The tasks include: classifying unmanned aerial vehicles according to the main features that determine their production specifics; analysing modern scientific publications in the field of distributed production informatization, multi-agent systems, digital twins and intelligent decision support; identifying the limitations of existing solutions; and proposing an approach to the organization of distributed production of UAVs using digital twins in the form of intelligent agents. The applied methods are based on system and classification analysis, generalization of modern scientific approaches to the organization of production, decision-making theory, the concept of multi-agent systems, digital twin technologies, production logistics and artificial intelligence. The following results were obtained: UAVs were classified by mass, purpose and level of autonomy, which made it possible to determine the specifics of their production and life cycle management. An analysis of scientific publications was performed, which showed the active development of areas related to the use of multi-agent systems, digital twins and artificial intelligence to address complex tasks in UAV life cycle management. It was established, in particular, that the works of recent years consider the issues of cooperative UAV production, the use of deep learning algorithms for decision-making in dynamic environments and the integration of digital twins into relevant production systems. At the same time, a number of limitations on the implementation of existing solutions were identified: insufficient formalization of business processes between production participants, weak integration of digital twins into production logistics, and the lack of self-organization mechanisms. An approach to solving the problem of effective organization of distributed UAV production is proposed. The architecture of a multi-agent decision support system for distributed UAV production is developed, which includes modules for coordination, self-organization, and the evaluation of the effectiveness of production configuration options, considering the initial risk tolerance indicator. Conclusions. The scientific novelty of the results obtained is as follows: an approach to solving the problem of effective organization of distributed UAV production is proposed, which, unlike existing ones, is based on the representation of production participants as digital twins in the form of intelligent agents, this enables the generation of multiple options and the subsequent selection of the most rational configuration for organizing distributed UAV production in terms of business process efficiency and the reduction of production risks. The research results create a basis for further integration of multi-agent technologies into real-world manufacturing platforms and the expansion of their application to other types of complex machinery.

A client-server network is one of the most important topics in a computer network. In this work, a real-time computer control system is designed based on the Client-Server Model for a Multi-Agent Mobile Robot System (CSM-MAMRS) and is applied to a building that consists of (N) floors and uses one mobile robot on each floor that has specific actions in different types of environments. The new proposed CSM-MAMRS consists of four layers. The first stage manages the network communication for each agent. The second stage solves the major problems of path planning by using a proposed hybrid algorithm that combines the Rapidly Exploring Random Tree Star (RRT*) and the Particle Swarm Optimization (PSO) algorithms in order to provide the shortest and smoothest path with collision avoidance between the starting and the target points in a static and dynamic robot environments are used.. In the third stage, a velocity planner controller is based on an inverse kinematic mobile robot model. In the fourth stage, the Hypertext Transfer Protocol HTTP is used to send velocity values to real mobile robots via the Wireless Network Control Administration. The simulation results and experimental works successfully achieved to significant improvement in real-time when using three missions of three mobile robots on different static map floors in the building. The maximum tracking pose errors for three robots in the static enviormnets are 0.39 cm, 0.02 cm, 0.32 cm respectively, but the maximum tracking pose error in the dynamic environments are 2.94 cm and 2.8 cm only for two mobile robots along the maximum distance of 250 cm. Index Terms— Real-time computer control, Mobile robot, Multi-agent system, Path planning algorithms.

Chapter 17 - Strategies and Prediction in Multi-Agent Systems

<div class="htmlview paragraph">This paper describes a software system called FREPS (Forced REsponse Prediction System) that integrates structural dynamic, steady and unsteady aerodynamic analyses to efficiently predict the forced response dynamic stresses in axial flow turbomachinery blades due to aerodynamic and mechanical excitations. A flutter analysis capability is also incorporated into the system. The FREPS system performs aeroelastic analysis by modeling the motion of the blade in terms of its normal modes. The structural dynamic analysis is performed by a finite element code such as MSC/NASTRAN. The steady aerodynamic analysis is based on nonlinear potential theory and the unsteady aerodynamic analysis is based on a linearization of the non-uniform potential mean flow. The program description and presentation of the capabilities are reported herein. The effectiveness of the FREPS package is demonstrated on the High Pressure Oxygen Turbopump turbine of the Space Shuttle Main Engine. Both flutter and forced response analyses are performed and typical results are illustrated.</div>

The dynamic analysis of structures with uncertain parameters presents an attractive field of structural health monitoring in many cases of technological interest. In the dynamic analysis of hydraulic structures, such as existing dams, modeling assumptions, resulting inaccuracies, and changes in seismic loading are typically the main sources of uncertainties. Many hydraulic structures of concrete can be subjected to seismic loads. However, it is necessary to take haphazard or random phenomena as crucial considerations when assessing the security of these structures or planning new ones. This paper shows computational analysis for the characterization of the behavior of a concrete gravity dam under seismic loads, which are considered sources of uncertainties. The multi-linear regression methodology was performed and applied to evaluate the dynamic response of the considered structure. Numerous nonlinear time history analyses based on Latin Hypercube Sampling were realized to investigate the effect of uncertain parameters on the dynamic response. These analyses were applied to two types of seismic actions, the near and far earthquakes, which act on a concrete gravity dam. Then, a sensitivity analysis was used for each random variable to quantify its risk and clarify its influence on the dynamic behavior of the dam. Results divulge that for near-fault cases, major variables affecting the global sensitivity across all limit states are the Young’s modulus of soil and concrete. On the other hand, for far-fault cases, the important variables influencing the global sensitivity index include the compressive strength of concrete, Young’s modulus of soil, and cohesion.

Role and member selection in team formation using resource estimation for large-scale multi-agent systems

Coordination of multiple autonomous robots is a typical research problem in Multi-agent systems. The distributed agent models that represent the supervisory controllers of autonomous soccer robots are capable of communication, interaction and collaboration. By introducing the multi-agent based control architecture, the soccer robots perform seamless team cooperation to achieve the desired mission during competition. Due to the multi-soccer robot system is a discrete event dynamic system with concurrent and asynchronous characteristics, the distributed agent-oriented Petri net (DAOPN) is selected in this paper to model and control the behaviors of the multi-soccer robot systems. The agent models proposed in this work consist of the coordination model and the skill oriented robot behavior models. Especially, the agent based communication places enable the distributed agent models to be communicated directly. In this manner, the DAOPN based agent models can act as the robot controllers and coordinator to perform run-time controls of the soccer robot team. Therefore, the proposed approach not only resolves problems of the multi-robot coordination, but also provides a feasible way to overcome the complicated mathematical functions or rule bases. Finally, this system is tested using four soccer robots, and the results verify the proposed DAOPN based controller. Index Petri nets, agent-based simulation and modeling, cooperation and coordination among agents.

Since the quality of data affects the success rate ofdata mining and learning algorithms, it is always attempted to identify and remove the irrelevant and redundant information in a dataset. Robotic soccer is a multi-agent system in which agents play in real-time, dynamic, complex and noisy environment. Many parameters affect the result of shooting toward the goal and agents must response to variations in soccer field rapidly. Therefore it is impossible to use all features in scoring behavior. This paper selects dataset for effective features of scoring behavior simulated soccer agents, then compares the size of the trees and accuracy produced by each feature selection scheme against the size of the trees and accuracy produced by C4.5 with no feature selection method. Experimental results have shown that dimensionality reductions lead to operate faster and more effective learning algorithm in real-time simulated soccer agent.

Purpose– The purpose of this paper is to design intelligent robots operating in such dynamic environments like the RoboCup Middle-Size League (MSL). In the RoboCup MSL, two teams of five autonomous robots play on an 18- × 12-m field. Equipped with sensors and on-board computers, each robot should be able to perceive the environment, make decision and control itself to play the soccer game autonomously.Design/methodology/approach– This paper presents the design of our soccer robots, participating in RoboCup MSL. The mechanical platform, electrical architecture and software framework are discussed separately. The mechanical platform is designed modularly, so easy maintainability is achieved; the electronic architecture is built on industrial standards using PC-based control technique, which results in high robustness and reliability during the intensive and fierce MSL games; the software is developed upon the open-source Robot Operating System (ROS); thus, the advantages of ROS such as modularity, portability and expansibility are inherited.Findings– Based on this paper and the open-source hardware and software, the MSL robots can be re-developed easily to participate in the RoboCup MSL. The robots can also be used in other research and education fields, especially for multi-robot systems and distributed artificial intelligence. Furthermore, the main designing ideas proposed in the paper, i.e. using a modular mechanical structure, an industrial electronic system and ROS-based software, provide a common solution for designing general intelligent robots.Originality/value– The methodology of the intelligent robot design for highly competitive and dynamic RoboCup MSL environments is proposed.

PurposeThe purpose of this paper is to briefly summarize and review the theories and methods of complex structures’ dynamic reliability. Complex structures are usually assembled from multiple components and subjected to time-varying loads of aerodynamic, structural, thermal and other physical fields; its reliability analysis is of great significance to ensure the safe operation of large-scale equipment such as aviation and machinery.Design/methodology/approachIn this paper for the single-objective dynamic reliability analysis of complex structures, the calculation can be categorized into Monte Carlo (MC), outcrossing rate, envelope functions and extreme value methods. The series-parallel and expansion methods, multi-extremum surrogate models and decomposed-coordinated surrogate models are summarized for the multiobjective dynamic reliability analysis of complex structures.FindingsThe numerical complex compound function and turbine blisk are used as examples to illustrate the performance of single-objective and multiobjective dynamic reliability analysis methods. Then the future development direction of dynamic reliability analysis of complex structures is prospected.Originality/valueThe paper provides a useful reference for further theoretical research and engineering application.

A unified framework for reinforcement learning, co-learning and meta-learning how to coordinate in collaborative multi-agent systems

Several agent frameworks have been proposed for developing intelligent software agents and multi-agent systems that are able to perform in dynamic environments. These frameworks and architectures exploit specific reasoning tasks (such as option selection, desire filtering, plan elaboration and means-end reasoning) that support agents to react, deliberate and/or interact/cooperate with other agents. Such reasoning tasks are realized by means of specific modules that agents may trigger according to circumstances, switching their behaviour between predefined discrete behavioural modes. This paper presents the facilities provided by the non-layered BDI-architecture of ICagent for supporting performance in dynamic and unpredictable multi-agent environments through efficient balancing between behavioural modes in a continuous space. This space is circumscribed by the purely (individual) reactive, the purely (individual) deliberative and the social deliberative behavioural modes. In a greater extend than existing frameworks; ICagent relates agent’s flexible behaviour to cognition and sociability, supporting the management of plans constructed by the agent’s mental and domain actions in a coordinated manner.