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IEEE International Conference on Robotics, Intelligent Systems and Signal Processing

作者： Jia, YP Wang, PX Li, Y Tai Yuan Heavy Machinery Inst Dept Machinery & Elect Engn Taiyuan 030024 Peoples R China

ISBN: (纸本)078037925X

A detailed introduction of intelligent inspection and monitoring system for Flexible Manufacturing System (FMS) based on distributed artificial intelligence(DAI) is given in this paper This paper deals with a multi-sensor system applied to mechanical fault diagnosing fusion pattern based on neural network, the uncertainty of diagnosis system can be decreased greatly. The methods for data preprocessing, features extraction and construction of the neural network are discussed The real-time data sampling, information fusion and control, management and decision, and operating process of the complex industrial systems are researched. The schemes of distributed hierarchical intelligent control, methods of multi-sensor in formation fusion and controller expert fuzzy neural networks are proposed for complex industrial process. Applying the redundancy technology and multi-sensor information fusion technology, the synchronized automated data acquisition, processing and malfunction warning is realized by computer. The results of application in a textile machinery plant for the FMS showed the effectiveness of the proposed hierarchical intelligent control system.

关键词： flexible manufacturing systems inspection fuzzy neural nets sensor fusion learning (artificial intelligence) fault diagnosis distributed control intelligent control fuzzy control diagnostic expert systems redundancy data acquisition textile industry flexible manufacturing system FMS fuzzy neural networks controller expert system multisensor data fusion intelligent inspection monitoring system distributed artificial intelligence DAI multisensor system mechanical fault diagnosing fusion pattern data preprocessing features extraction real time data sampling complex industrial systems decision making distributed hierarchical intelligent control system multisensor information fusion technology complex industrial process redundancy technology automated data acquisition malfunction warning textile machinery plant

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Decentralized Energy Sharing Protocol using TÆMS Framework and Coalition-based Metaheuristic for Heterogeneous Robotic Systems

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IFAC-PapersOnLine 2017年第1期50卷 5914-5919页

作者： Arbanas B. Boljuncic S. Petrovic T. Bogdan S. University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Croatia

In this paper we describe a decentralized protocol that is applied for scheduling and management of energy sharing in heterogeneous systems. Particular system we have in mind comprises of agents with different mobility, energy harvesting and energy sharing capabilities herein called aPads, aFish and aMussels. aPads are surface vehicles that harvest energy and are able to transmit it to both aFishes and aMussels. aFish are underwater vehicles that can transmit energy to aMussels or to other aFish, and receive energy from aPads. aMussels, that can either be attached to the sea-ground or float on the surface, can only receive energy, either from aFish or aPads. For such a system to be able to function for an extended period of time, a decentralized energy management protocol should be designed, whose purpose is to schedule and coordinate charging of agents over time. These decisions depend on the current battery levels of different agents, as well as their positions, and should be done in a decentralized manner. In this paper we apply an energy sharing protocol based on TÆMS framework, originally applied to planning and coordination in aerial-ground robotics systems for search and rescue missions. We refine the obtained plans using the coalition-based metaheuristic for vehicle routing problems. We show execution schedules achieved using the proposed protocol and highlight its advantages and flaws when applied to our underwater scenario. © 2017

关键词： decentralized systems distributed artificial intelligence Hierarchical decision making scheduling algorithms

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Self-Organization for Search in Peer-to-Peer Networks: The Exploitation-Exploration Dilemma

Self-Organization for Search in Peer-to-Peer Networks: The E...

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1st International Conference on Bio-Inspired Models of Network, Information and Computing Systems

作者： Michlmayr, Elke Vienna Univ Technol Womens Postgrad Coll Internet Technol WIT Inst Software Technol & Interact Syst Favoritenstr 9-11-E188 A-1040 Vienna Austria

ISBN: (纸本)1424404630

This paper presents the design and evaluation of an ant-based approach to query routing in peer-to-peer networks. After pointing out how to employ the ant metaphor in peer-to-peer networks, we conduct a thorough evaluation of the impact of different settings for the configurable parameters present in ant algorithms on the performance values. In particular, the focus is on the effects of setting the ratio between (1) ants exploiting the option currently known as the best one and (2) ants exploring the search space with the aim of finding improved options. We show that the exploitation-exploration dilemma can be avoided by an adequate design of the exploring option.

关键词： Self-Organization Peer-to-Peer Networks Ant Colony Optimization Exploration Exploitation distributed artificial intelligence Multi-Agent Systems

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MACSIMA: On the Effects of Adaptive Negotiation Behavior in Agent-Based Supply Networks

MACSIMA: On the Effects of Adaptive Negotiation Behavior in ...

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7th German Conference on Multi-Agent System Technologies

作者： Russ, Christian Walz, Alexander Dacos Software GmbH Sci Pk 2 D-66123 Saarbrucken Germany Univ Stuttgart Graduate Sch of Excellence Adv Manufacturing Engn D-70174 Stuttgart Germany

ISBN: (纸本)9783642041426

In this paper, we describe the multiagent supply chain simulation framework MACSIMA that allows the design of large-scale supply network topologies consisting of a multitude of autonomous agents. MACSIMA provides all agents with an adaptive negotiation module providing the fine-tuning of learning capabilities on the basis of genetic algorithms as well as of settings controlling the exchange of information about finished negotiations with other cooperating agents. On this basis the co-evolution and adaptation of price negotiation strategies as well as coalition formation processes of self-interested business agents in B2B-networked domains can be fine-tuned, simulated and evaluated. Our evaluation of the effects of self-adaptation on the overall turnover and profit of a live-tier supply network scenario shows that coordination outcome and efficiency vary significantly in dependence on (a) the elaborateness of used learn parameterizations, (b) on the homogeneity of the distribution of learn parameter settings within the agent society and (c) on the information exchange settings. System outcomes are measured on a macro-level in overall turnover, profit, and communication efficiency as well as on a group-level in the distributed group portions on turnover and profit. Our analysis shows, that an expert learn and information exchange parameterization of the agents results in an increase of the overall system outcome in sales and profit by approx. 500 percent and thus has to be fine-tuned for reaching an efficient and effective coordination outcome. Moreover, expert parameterizations result in an improved communication efficiency and outcome stability on the macro- and the group-level. Providing a subgroup of agents with superior learn capabilities results in a shift of sales and profit to the smarter agents.

关键词： distributed artificial intelligence Multiagent Systems Simulation Modeling and Output Analysis Intelligent Agents Evolutionary Learning Experimental Economics Agent-based Supply Chain Management Coordination Mechanism Design Bilateral Negotiation Genetic Algorithms

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A Dynamic MAS to Manage a Daily Planning for a Team Operating Theater 2nd

A Dynamic MAS to Manage a Daily Planning for a Team Operatin...

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3rd International Conference on Digital Technologies and Applications

作者： Soualfi, Oumaima Hajji Soualfi, Abderrahim Hajji Chmali, Khalid Elmrini, Abdelmajid Elbarkany, Abdellah Harras, Bilal Sidi Mohamed Ben Abdellah Univ Fac Sci & Tech Mech Engn Lab Fes Morocco Moulay Ismail Univ Fac Sci & Tech Dept Sci Comp Errachidia Morocco Sidi Mohamed Ben Abdellah Univ Hassan II Univ Hosp Fac Med & Pharm Fez Dept Orthoped Surg B4 Fes Morocco

ISBN: (纸本)9783031298561;9783031298578

Surgical planning is a preponderant step in the management of operating theaters, which becomes more and more solicited;considering the multiplicity and the complexity of the human and material components, which intervene there;in order to face the various disturbances hindering the normal course of the surgical activity. It is a subject widely discussed in the literature with the realization of several solutions and applications, but which remain globally incompatible with the realities of the surgical process. For this reason, we propose a daily surgical planning realized with a multi-agent system (MAS) based on distributed artificial intelligence (DAI). We describe some basic architectural entities of MAS in relation with the surgical planning, before presenting their application on a real case of the orthopedic surgery department B4 of the CHU Hassan II of Fez-Morocco. The objective of this work is to elaborate a daily, dynamic and real time surgical program answering the various possible and frequent disturbances altering the process of the operating theater.

关键词： multi-agent system distributed artificial intelligence operating theater planning

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Load balancing in distributed computing systems using fuzzy expert systems

Load balancing in distributed computing systems using fuzzy ...

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International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET 2002)

作者： El-Abd, AE Alexandria Inst Technol Dept Comp Engn Alexandria Egypt

ISBN: (纸本)9665532340

In this paper we present fuzzy functions to model load balancing in distributed computing systems. Due to lack of communication delays in message passing, a complete and consistent view of the entire system may never be available to a node of the system. Most of the previous work in load balancing and distributed decision making in general, do not effectively take into account the uncertainty and inconsistency in state information. Also both the load patterns and task lengths descriptions are based on crisp values which may be inconvenient. Most of the research that used fuzzy descriptions considered fixed fuzzy function parameter values that only can match in fixed load patterns. The aim of this paper is to solve the uncertainty problem in state information and task selection for migration using proposed fuzzy functions of variable membership values, and to propose an expert system that uses these fuzzy functions in decision making.

关键词： artificial intelligence distributed artificial intelligence fuzzy logic expert systems

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Designing EEPO: An Emissary Educator Playmate Oracle XR Conversation Agent for Children

Designing EEPO: An Emissary Educator Playmate Oracle XR Conv...

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IEEE Conference on Virtual Reality and 3D User Interfaces (VR)

作者： Zhang, Jessy Morris, Alexis Martyn, Nikki Zaccolo, Sandro OCAD Univ Adapt Context Environm ACE Lab Toronto ON Canada Univ Guelph Humber Early Childhood Studies Toronto ON Canada SZID Inc Toronto ON Canada

ISBN: (纸本)9798350374490;9798350374506

This paper presents an extended reality (XR) embodied conversational agent, as a social-emotional companion for parents and children within the home context. It has focused on the role of technology including artificial intelligence ( Al) and XR on holistic child development and well-being. parenting, and the beautiful relational space in between children and parents, here termed Augmented Sociology. Based on the EEPO (Emissary Educator Playmate Oracle) theoretical child technology interaction framework, this work presents an early EEPO prototype, toward an XR social-emotional development companion agent for children and support agent for parents.

关键词： Human-centered computing Human computer interaction (HCI) Interaction paradigms Mixed / augmented reality Human-centered computing Human computer interaction (HCI) Interaction paradigms Natural language interfaces Computing methodologies artificial intelligence distributed artificial intelligence Intelligent agents Applied computing Law, social and behavioral sciences Sociology

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Research of communication mechanism of multi-agent robot systems

Research of communication mechanism of multi-agent robot sys...

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12th International Symposium on Micromechatronics and Human Science (MHS2001)

作者： Gao, ZJ Yan, GZ Ding, GQ Huang, H Shanghai Jiao Tong Univ Coll Elect & Informat Shanghai 200030 Peoples R China

ISBN: (纸本)0780371909

The cooperation of multi-robot that is based on the Multi-Agent System (MAS) theory of distributed artificial intelligence has become a hotspot in the robotics R&D. In the research, the communication and cooperation of multi-agent become the key problem for gaining the dynamic running information of cooperating robots. In this paper we introduce the communication modes for agent and provide a common strategy (which aims at the communication resources of multi-agent model) - the CSMA/CD (Carrier Sense Multiple Access with Collision Detection) protocol which is based on the transmittal medium. It supports the cable-communication of multi-robot and the experiments prove its validity.

关键词： carrier sense multiple access multi-robot systems multi-agent systems mobile robots collision avoidance protocols local area networks telecommunication network routing communication mechanism multi-agent robot systems cooperation distributed artificial intelligence robotics R&D carrier sense multiple access with collision detection protocol CSMA/CD protocol cable-communication

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On the Application of Game theory for Multiagent system-based Cognitive Performance Management in Software-defined networks 11

On the Application of Game theory for Multiagent system-base...

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11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)

作者： Goldshtein, Boris S. Elagin, Vasiliy S. Nguyen, Cong D. Onufrienko, Anastasia V. Bonch Bruevich St Petersburg State Univ Telecommu Infocommun Syst Dept St Petersburg Russia

ISBN: (纸本)9781728157634

Nowadays, cognitive multiagent self-organization is the subject of intensive research in the field of info-communication technology. This state-of-the-art in constructing distributed intelligent systems for telecommunication management is already receiving attention both from researchers and from industrial application developers. The purposes of this work are to present the implementation of a game theory-based cognitive model for network performance management, to analyze the possibilities of using this model in dynamic orchestration and resource allocation use cases in software-defined networks. Thus, special attention has been devoted to the developed multiagent management system architecture, the stages of which form various game-theoretic models with the participation of intelligent software agents, designed to organize automated coordination of requests from the application layer to the corresponding network resources.

关键词： multiagent MAS distributed artificial intelligence game theory self-organization performance management SDN

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QDDS – A Novel Quantum-Inspired Swarm Optimizer: Theoretical Foundations, Convergence Analyses and Application Perspectives

QDDS – A Novel Quantum-Inspired Swarm Optimizer: Theoretica...

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作者： Sengupta, Saptarshi Vanderbilt University

学位级别：Ph.D.

With sensor fusion and data-driven approaches taking center stage in ubiquitous computing, customized and application-specific optimization methods are increasingly important. The interest follows in part from the limitations of specific optimization methods implied by the No Free Lunch Theorem. Applications of computational intelligence are growing exponentially with the widespread availability of increasingly powerful computers. This has made feasible the mimicry of highly interactive multi-agent models of natural systems that solve complicated problems while remaining stable. The emergent behaviors arising in such systems hint at novel methods of optimization that can find solutions to machine learning problems of similar complexity. This dissertation introduces a social, agent-based (swarm) intelligence algorithm viz. the Quantum Double Delta Swarm (QDDS). It is modeled after the mechanism of convergence, under an attractive potential field, to the center of a single well in a double Dirac delta potential-well problem. The swarming model developed here extends the well-known Quantum-behaved Particle Swarm Optimization (QPSO) algorithm to the more stable, double well configuration for optimal solutions of complex engineering design problems. Theoretical foundations and experimental illustrations lead to applications of the model to find solutions of problems in intrinsically high-dimensional feature spaces. In addition, the effects of chaos on the exploratory capacity of the algorithm are studied by including a Chebyshev map driven exploration (C-QDDS) step and benchmarking the results. Visualization of the process is enabled by tracking the trajectory of the best performing agent in each iteration over all episodes across benchmark contours. Under general assumptions common to random search convergence proofs the dynamical limitations of this model’s convergence are critically analyzed. Finally, results are demonstrated on: a) the multidimensional finite impulse

关键词： quantum-inspired computational intelligence stochastic optimization particle swarm optimization multiagent systems swarm intelligence distributed artificial intelligence

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