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Requirements for the design of a protocol suite to automate DSS deployment on the World Wide Web: A client/server approach

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DECISION SUPPORT SYSTEMS 1997年第3期19卷 151-170页

作者： Goul, M Philippakis, A Kiang, MY Fernandes, D Otondo, R Computer Information Systems Area School of Accountancy College of Business Arizona State University Tempe AZ 85287-3606 USA

The purpose of this paper is to propose and justify requirements for the design of a protocol suite for deploying and sharing Specific DSSs both within and across organizations by utilizing the World Wide Web (WWW) infrastructure and a client/server decomposition model. At the heart of the model proposed for the protocol suite is an approach for inter-agent communication as adapted from the distributed artificial intelligence literature. A modularized layered approach to protocol specification, and three sample client interfaces derived from the protocol are presented. Our approach is contrasted to alternative schemes for decision model access across wide area networks.

关键词： decision support system Internet protocol distributed artificial intelligence

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distributed Neural Networks for Signal Change Detection: On the Way to Cognition in Sensor Networks

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IEEE SENSORS JOURNAL 2011年第3期11卷 791-798页

作者： Reznik, Leon Von Pless, Gregory Al Karim, Tayeb Rochester Inst Technol Rochester NY 14623 USA

Cognition is a fundamental feature of natural intelligence, which a modern technology has not yet been able to reproduce in full capacity. Sensor networks provide a new technological support for a substantial increase in an amount and quality of information that might be collected and communicated in complex adaptive systems. Their application may significantly raise the degree of intelligence in system design and implementation into the levels where effects of cognition will start kicking in. The paper describes the results of an empirical study aiming to demonstrate that a cognition ability may be treated as a generic sensor network feature. The new architecture with neural networks distributed over the sensor network platforms was developed for sensor network engineering applications. The detection system learns to detect the change of not only the signal levels but also sensor signal shapes and parameters that represent a more complicated task. The architecture allows for a significant reduction in resource consumption without compromising the change detection performance. Implemented as an agent controlling the sensor network self-adjustment to the objects under measurement in the sensor network composed from typical sensor motes, the novel neural network structures may achieve a significant saving in power consumption and an increase in a possible network deployment time from a few days to a few years. The experiments prove that a neural-network-based change detection system is feasible for sensor networks application designs and could be successfully implemented on the technological platforms currently available on the market.

关键词： artificial neural networks (ANNs) distributed artificial intelligence sensor networks signal change detection

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Wireless Federated Learning (WFL) for 6G Networks-Part I: Research Challenges and Future Trends

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IEEE COMMUNICATIONS LETTERS 2022年第1期26卷 3-7页

作者： Bouzinis, Pavlos S. Diamantoulakis, Panagiotis D. Karagiannidis, George K. Aristotle Univ Thessaloniki Wireless Commun & Informat Proc Grp WCIP Dept Elect & Comp Engn Thessaloniki 54124 Greece

Conventional machine learning techniques are conducted in a centralized manner. Recently, the massive volume of generated wireless data, the privacy concerns and the increasing computing capabilities of wireless end-devices have led to the emergence of a promising decentralized solution, termed as Wireless Federated Learning (WFL). In this first of the two parts letter, we present the application of WFL in the sixth generation of wireless networks (6G), which is envisioned to be an integrated communication and computing platform. After analyzing the key concepts of WFL, we discuss the core challenges of WFL imposed by the wireless (or mobile communication) environment. Finally, we shed light to the future directions of WFL, aiming to compose a constructive integration of FL into the future wireless networks.

关键词： Wireless federated learning distributed artificial intelligence 6G networks

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From intelligent agents to trustworthy human-centred multiagent systems

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AI COMMUNICATIONS 2022年第4期35卷 443-457页

作者： Soorati, Mohammad Divband Gerding, Enrico H. Marchioni, Enrico Naumov, Pavel Norman, Timothy J. Ramchurn, Sarvapali D. Rastegari, Bahar Sobey, Adam Stein, Sebastian Tarpore, Danesh Yazdanpanah, Vahid Zhang, Jie Univ Southampton Sch Elect & Comp Sci Agents Interact & Complex Res Grp Southampton Hants England

The Agents, Interaction and Complexity research group at the University of Southampton has a long track record of research in multiagent systems (MAS). We have made substantial scientific contributions across learning in MAS, game-theoretic techniques for coordinating agent systems, and formal methods for representation and reasoning. We highlight key results achieved by the group and elaborate on recent work and open research challenges in developing trustworthy autonomous systems and deploying human-centred AI systems that aim to support societal good.

关键词： Multiagent systems intelligent agents distributed artificial intelligence trustworthy autonomous systems

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Hiding in the Crowd: Federated Data Augmentation for On-Device Learning

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IEEE INTELLIGENT SYSTEMS 2021年第5期36卷 80-86页

作者： Jeong, Eunjeong Oh, Seungeun Park, Jihong Kim, Hyesung Bennis, Mehdi Kim, Seong-Lyun Yonsei Univ Seoul 03722 South Korea Deakin Univ Sch IT Waurn Ponds Vic 3216 Australia Samsung Res Seoul 06765 South Korea Univ Oulu Ctr Wireless Commun Oulu 90570 Finland Yonsei Univ Sch Elect & Elect Engn Seoul 03722 South Korea

To cope with the lack of on-device machine learning samples, this article presents a distributed data augmentation algorithm, coined federated data augmentation (FAug). In FAug, devices share a tiny fraction of their local data, i.e., seed samples, and collectively train a synthetic sample generator that can augment the local datasets of devices. To further improve FAug, we introduce a multihop-based seed sample collection method and an oversampling technique that mixes up collected seed samples. Both approaches enjoy the benefit from the crowd of devices, by hiding data privacy from preceding hops and feeding diverse seed samples. In the image classification tasks, simulations demonstrate that the proposed FAug frameworks yield stronger privacy guarantees, lower communication latency, and higher on-device ML accuracy.

关键词： Servers Privacy Data models Training Intelligent systems distributed databases Generators Machine learning distributed networks distributed artificial intelligence Wireless communication

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Multi robot distance based formation using Parallel Genetic Algorithm

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APPLIED SOFT COMPUTING 2020年 86卷

作者： Lopez-Gonzalez, A. Meda Campana, J. A. Hernandez Martinez, E. G. Paniagua Contro, P. Inst Politecn Nacl SEPI ESIME Zacatenco Ave IPN S-N Cdmx 07738 DF Mexico Univ Iberoamer DICAT Prolongac Paseo Reforma 880 Cdmx 01219 Mexico

In this paper an alternative method to achieve distance based formation is presented. The method uses Genetic Algorithms to find a suitable solution based on angle and distance, and an appropriate constant velocity to avoid collisions. The designed algorithm is extended to a parallel scheme to improve its performance and achieve artificial distributed intelligence, in which the robots share, through solution migration, the best ways to converge to desired distances while avoiding collisions, finally reaching consensus on the solution. The algorithm is tested using simulations and real robots experiments. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Parallel Genetic Algorithm Multi robot Consensus Formation distributed artificial intelligence

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MAKRS - A KNOWLEDGE AND BELIEF REPRESENTATION SYSTEM FOR MULTIPLE AGENTS

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KNOWLEDGE-BASED SYSTEMS 1994年第2期7卷 91-102页

作者： KIM, YH MAENG, SR CHO, JW Department of Computer Science Korea Advanced Institute of Science and Technology 373-1 Kusong-dong Yusong-gu Taejon 305-701 Korea

The paper presents a knowledge and belief representation system for multiple agents called MAKRS. MAKRS can represent and reason about multi-agent knowledge and belief as well as factual knowledge of the actual world. It can also process some axioms which are usually used to represent the characteristics of each agent's knowledge and belief. MAKRS can be used as a tool to construct knowledge bases for various applications where multiple agents co-exist, and some sample knowledge bases are constructed to demonstrate its usefulness and practicality.

关键词： INFORMATION SYSTEMS KNOWLEDGE REPRESENTATION SYSTEMS MULTIAGENT SYSTEMS KNOWLEDGE AND BELIEF distributed artificial intelligence

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Application of artificial Capital Market in Task Allocation in Multi-robot Foraging

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INTERNATIONAL JOURNAL OF COMPUTATIONAL intelligence SYSTEMS 2014年第3期7卷 401-417页

作者： Akbarimajd, Adel Simzan, Ghader Univ Mohaghegh Ardabili Fac Engn Dept Elect Engn Ardebil Iran Islamic Azad Univ Meshkin Shahr Branch Meshkin Shar Iran

Because of high speed, efficiency, robustness and flexibility of multi-agent systems, in recent years there has been an increasing interest in the art of these systems. artificial market mechanisms are one of the well-known negotiation multi-agent protocols in multi-agent systems. In this paper artificial capital market as a new variant of market mechanism is introduced and employed in a multi-robot foraging problem. In this artificial capital market, the robots are going to benefit via investment on some assets, defined as doing foraging task. Each investment has a cost and an outcome. Limited initial capital of the investors constrains their investments. A negotiation protocol is proposed for decision making of the agents. Qualitative analysis reveals speed of convergence, near optimal solutions and robustness of the algorithm. Numerical analysis shows advantages of the proposed method over two previously developed heuristics in terms of four performance criteria.

关键词： Task Allocation Foraging Robots distributed artificial intelligence Multi-agent Systems Capital Market Mechanism

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A migration-based approach towards resource-efficient wireless structural health monitoring

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ADVANCED ENGINEERING INFORMATICS 2013年第4期27卷 625-635页

作者： Smarsly, Kay Law, Kincho H. Bauhaus Univ Weimar Dept Civil Engn D-99423 Weimar Germany Stanford Univ Dept Civil & Environm Engn Stanford CA 94305 USA

Wireless sensor networks have emerged as a complementary technology to conventional, cable-based systems for structural health monitoring. However, the wireless transmission of sensor data and the on-board execution of engineering analyses directly on the sensor nodes can consume a significant amount of the inherently restricted node resources. This paper presents an agent migration approach towards resource-efficient wireless sensor networks. Autonomous software agents, referred to as "on-board agents", are embedded into the wireless sensor nodes employed for structural health monitoring performing simple resource-efficient routines to continuously analyze, aggregate, and communicate the sensor data to a central server. Once potential anomalies are detected in the observed structural system, the on-board agents autonomously request for specialized software programs ("migrating agents") that physically migrate to the sensor nodes to analyze the suspected anomaly on demand. In addition to the localized data analyses, a central information pool available on the central server is accessible by the software agents (and by human users), facilitating a distributed-cooperative assessment of the global condition of the monitored structure. As a result of this study, a 95% reduction of memory utilization and a 96% reduction of power consumption of the wireless sensor nodes have been achieved as compared with traditional approaches. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Structural health monitoring Wireless sensor networks Smart structures distributed artificial intelligence Mobile multi-agent systems Dynamic wireless code migration

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Provenance in agent-mediated healthcare systems

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IEEE INTELLIGENT SYSTEMS 2006年第6期21卷 38-46页

作者： Kifor, Tamas Varga, Laszlo Z. Vazquez-Salceda, Javier Alvarez, Sergio Willmott, Steven Miles, Simon Moreau, Luc Comp & Automat Res Inst H-1111 Budapest Hungary Univ Politecn Cataluna Dept Llenguatges & Sist Informat E-08034 Barcelona Spain Univ Southampton Southampton SO9 5NH Hants England

People are increasingly cooperating to share electronic information and techniques throughout various industries. In healthcare applications, data (a single patient's healthcare history), workflow (procedures carried out on that patient), and logs (a recording of meaningful procedural events) are often distributed among several heterogeneous and autonomous information systems. Understanding a patient's treatment history can help healthcare providers make treatment decisions. Provenance-aware applications can facilitate this process by tracing events, event dependencies, and provider decisions across various healthcare institutions

关键词： Decision Making distributed Processing Health Care Medical Information Systems Multi Agent Systems Object Oriented Programming Patient Treatment Software Agents Agent Mediated Healthcare System Electronic Information Sharing Patient Healthcare History Patient Workflow Patient Log Heterogeneous Autonomous Information System Patient Treatment History Provenance Aware Application Event Tracing Event Dependency Healthcare Provider Decision Medical Services Medical Treatment History Documentation Information Systems Hospitals Automation Industrial Electronics Computer Industry Electronics Industry Computing Methodologies artificial intelligence distributed artificial intelligence Intelligent Agents Computer Applications Life And Medical Sciences Medical Information Systems Computer Applications Internet Applications Healthcare Information Technology And Systems Information Technology And Systems Applications Workflow Management Data Dependencies Information Technology And Systems Database Management Workflow Management Provenance

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