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4 Papers

Designing Distributed Multi-Agent System for Aggregate and Final Assembly of Complex Technical Objects on Ramp-up Stage

Topics: Multi-Agent Systems; Distributed Problem Solving; Task Planning and Execution; Agent Platforms and Interoperability

Authors: Petr Skobelev 1 , Valery Eliseev 2 , Igor Mayorov 3 , Vitaly Travin 4 , Alexey Zhilyaev 5 and Elena Simonova 5

Affiliations: 1 Samara National Research University and Samara State Technical University, Russian Federation , 2 Smart Solutions and Ltd, Russian Federation , 3 Smart Solutions, Ltd and Samara State Technical University, Russian Federation , 4 Samara National Research University, Russian Federation , 5 Smart Solutions, Ltd and Samara National Research University, Russian Federation

Digital Object Identifier: 10.5220/0006636202500257

Proceedings of ICAART 2018, ISBN: 978-989-758-275-2

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The paper covers the problem of aggregate and final assembly of complex technical objects at the ramp-up stage. New models, methods and tools for distributed scheduling are proposed, including modified version of virtual market with new classes of agents. The new feature of multi-agent scheduler considers knowledge base technology which helps to specify each operation in more detailed and individual way. The paper describes first system prototype for adaptive planning at the ramp-up stage and the main directions of future system development.
Collapse Button Related Ontology Subjects/Areas/Topics (13)
Agent Platforms and Interoperability

Distributed Problem Solving

Multi-Agent Systems

Agents

Enterprise Information Systems

Software Engineering

Artificial Intelligence

Knowledge Engineering and Ontology Development

Symbolic Systems

Artificial Intelligence and Decision Support Systems

Knowledge-Based Systems

Task Planning and Execution
Distributed and Mobile Software Systems

Measuring Adaptability of ”Swarm Intelligence” for Resource Scheduling and Optimization in Real Time

Topics: Multi-Agent Systems; Planning and Scheduling; Evolutionary Computing; Distributed Problem Solving; Agent Platforms and Interoperability; Self Organizing Systems

Authors: Petr Skobelev 1 , Igor Mayorov 2 , Sergey Kozhevnikov 3 , Alexander Tsarev 2 and Elena Simonova 4

Affiliations: 1 Software Engineering Company «Smart Solutions» and Ltd., Russian Federation , 2 Smart Solutions, Ltd and Samara State Technical University, Russian Federation , 3 SEC “Smart Solutions”, Russian Federation , 4 Samara State Aerospace University, Russian Federation

Digital Object Identifier: 10.5220/0005276605170522

Proceedings of ICAART 2015, ISBN: 978-989-758-074-1

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In this paper modern methods of scheduling and resource optimization based on the holonic approach and principles of “Swarm Intelligence” are considered. The developed classes of holonic agents and method of adaptive real time scheduling where every agent is connected with individual satisfaction function by the set of criteria and bonus/penalty function are discussed. In this method the plan is considered as a un-stable equilibrium (consensus) of agents interests in dynamically self-organized network of demands and supply agents. The self-organization of plan demonstrates a “swarm intelligence” by spontaneous autocatalitical reactions and other not-linear behaviours. It is shown that multi-agent technology provides a generic framework for developing and researching various concepts of “Swarm Intelligence” for real time adaptive event-driving scheduling and optimization. The main result of research is the developed approach to evaluate the adaptability of “Swarm Intelligence” by measuring improve of value and transition time from one to another unstable state in case of disruptive events processing. Measuring adaptability helps to manage self-organized systems and provide better quality and efficiency of real time scheduling and optimization. This approach is under implementation in multi-agent platform for adaptive resource scheduling and optimization. The results of first experiments are presented and future steps of research are discussed.
Collapse Button Related Ontology Subjects/Areas/Topics (21)
Agent Platforms and Interoperability

Enterprise Information Systems

Multi-Agent Systems

Agents

Evolutionary Computing

Planning and Scheduling

Artificial Intelligence

Formal Methods

Self Organizing Systems

Artificial Intelligence and Decision Support Systems

Informatics in Control, Automation and Robotics

Simulation and Modeling

Computational Intelligence

Intelligent Control Systems and Optimization

Soft Computing

Distributed and Mobile Software Systems

Knowledge Engineering and Ontology Development

Software Engineering

Distributed Problem Solving

Knowledge-Based Systems

Symbolic Systems

Real Time Scheduling of Data Transmission Sessions in a Microsatellites Swarm and Ground Stations Network Based on Multi-Agent Technology

Topics: Evolutionary Robotics and Intelligent Agents; Co-Evolution and Collective Behavior; Swarm/Collective Intelligence

Authors: P. Skobelev 1 , E. Simonova 1 , A. Ivanov 2 , I. Mayorov 3 , V. Travin 3 and A. Zhilyaev 1

Affiliations: 1 Samara State Aerospace University, SEC “Smart Solutions" and Ltd, Russian Federation , 2 École Polytechnique Fédérale de Lausanne, Switzerland , 3 SEC “Smart Solutions" and Ltd, Russian Federation

Digital Object Identifier: 10.5220/0005034301530159

Proceedings of ECTA 2014/IJCCI, ISBN: 978-989-758-052-9

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The problem of designing an effective models and methods for data transmission between group of microsatellites and network of ground stations in the dynamically changing environment is considered. Multi-agent technology for solving the problem by adaptive resource allocation and scheduling is proposed. It is shown that solution of the considered complex problem evolutionary emerges from interaction and trade-offs of many agents which continuously self-organize themselves and change decisions to improve their objectives and the objectives of the system as a whole. The advantages of multi-agent solution are high adaptability, flexibility and efficiency of services. The main classes of agents, ontology of problem domain, interaction protocols, results of first experiments with system prototype and key benefits of proposed system are discussed.
Collapse Button Related Ontology Subjects/Areas/Topics (7)
Artificial Intelligence

Evolutionary Computing

Soft Computing

Co-Evolution and Collective Behavior

Evolutionary Robotics and Intelligent Agents

Swarm/Collective Intelligence
Computational Intelligence

Comparing Adaptive and Non-adaptive Models of Cargo Transportation in Multi-agent System for Real Time Truck Scheduling

Topics: Evolutionary Robotics and Intelligent Agents; Co-Evolution and Collective Behavior; Swarm/Collective Intelligence

Authors: Oleg Granichin 1 , Petr Skobelev 2 , Alexander Lada 2 , Igor Mayorov 2 and Alexander Tsarev 2

Affiliations: 1 Saint Petersburg State University, Russian Federation , 2 Software Engineering Company «Smart Solutions» and Ltd., Russian Federation

Digital Object Identifier: 10.5220/0004148602820285

Proceedings of ECTA 2012/IJCCI, ISBN: 978-989-8565-33-4

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The application of multi-agent platform for real-time adaptive scheduling of trucks is considered. In case of unpredictable events the system works adaptively and doesn’t stop to restart the plan from the beginning. Different models of cargo transportation for truck companies having own fleet are analysed. The results show that using adaptive scheduling in real time it is possible to create significantly more profitable schedules (up to 40-60% compared with rigid models) and save a number of trucks (up to 20%) for the same amount of orders.
Collapse Button Related Ontology Subjects/Areas/Topics (7)
Artificial Intelligence

Evolutionary Computing

Soft Computing

Co-Evolution and Collective Behavior

Evolutionary Robotics and Intelligent Agents

Swarm/Collective Intelligence
Computational Intelligence

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