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Agent-oriented programming in defence domain

DEFENCE SCIENCE JOURNAL 2003年第3期53卷 267-273页

作者： Doiphode, S Res & Dev Estab Engn Pune 411015 Maharashtra India

Research in distributed artificial intelligence has given rise to agent-oriented programming (AOP), an advanced software modelling paradigm. It has several benefits when compared with the existing development approaches, in particular, the ability to let agents represent high-level abstractions of active entities in a software system. Although still young and under evolution, this paradigm has already shown particular promise in a number of areas. This paper gives an overview of this paradigm, its benefits over the other conventional programming paradigms being used. It also proposes the decision support system model for the military domain. In the proposed system there are certain critical issues, which need to be focused upon, The existing conventional paradigms are inadequate to deal with these issues. This paper identifies these critical issues and discusses how AOP can address these issues.

关键词： agent-oriented programming distributed artificial intelligence artificial intelligence decision support system object-oriented programming JAVA intelligent agents mobile agents BDI agent

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REDSIEX: A cooperative network of expert systems with blackboard architectures

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EXPERT SYSTEMS 1997年第4期14卷 180-189页

作者： Perez, PPG Martinez, JN XALAPA CTR MAESTRIA INTELIGENCIA ARTIFICIA UVXALAPAVERACRUZMEXICO

The blackboard architecture, originally developed for the system that permits the comprehension of language, HEARSAY II, has later been used in a great variety of domains and in various environments for the construction of systems. Front the classic architecture of HEARSAY II, many applications, generalizations, extensions and refinements hare been developed. Ill this paper we present REDSIEX, (RED de Slstemas EXpertos) which is a network of expert systems within a blackboard architecture, for rite cooperative solution of distributed problems. The REDSIEX system inherits various of the elements defined by the architecture of HEARSAY II and incorporates were components and organization. These produce a very characteristic and exclusive global work style in the solution of problems, within a conceptual framework of of emergent control. The main structural and functional characteristics of REDSIEX are discussed.

关键词： blackboard architecture cooperative systems distributed artificial intelligence emergent cooperation

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Hierarchical Deployment Optimization for Wireless Sensor Networks

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2011年第7期10卷 1028-1041页

作者： Wang, Xue Wang, Sheng Tsinghua Univ State Key Lab Precis Measurement Technol & Instru Dept Precis Instrument Beijing 100084 Peoples R China

Sensor nodes deployment is very crucial for wireless sensor networks (WSNs). Current methods are apt to enlarge the coverage by achieving a nearly even deployment with similar density in the whole network. However, in some specific applications, the even distribution may not satisfy the sensing requirements. This paper proposes a virtual force directed coevolutionary particle swarm optimization (VFCPSO) algorithm, which uses a combined objective function to achieve the tradeoff of coverage and energy consumption. By considering deployment as an optimization problem, VFCPSO is more reliable and flexible for WSNs, since it can satisfy the combined requirements instead of only enlarging coverage. For investigating the performance of different paradigms, centralized VFCPSO is extended to distributed VFCPSO, heterogeneous hierarchical VFCPSO and homogeneous hierarchical VFCPSO (Homo-H-VFCPSO), and the solution of preferential deployment in interested region is also analyzed. Simulation results show that the Homo-H-VFCPSO has the best performance, i.e., it is more efficient than other three VFCPSO algorithms and the VF-style algorithms in terms of computation time, coverage and efficient moving energy consumption. It is obvious that the Homo-H-VFCPSO has good global searching ability and scalability, and it can rapidly and effectively achieve the sensor nodes deployment in WSNs.

关键词： Wireless sensor networks deployment particle swarm optimization distributed artificial intelligence

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Modeling and simulating terrorist networks in social and geospatial

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IEEE INTELLIGENT SYSTEMS 2007年第5期22卷 40-49页

作者： Moon, Il-Chul Carley, Kathleen M. Carnegie Mellon Univ Sch Comp Sci Pittsburgh PA 15213 USA

A simple theoretical multiagent model reasons about the criticality of terrorists and regions as terrorist interactions coevolve in geographical and social spaces. Social and spatial relations evolve over time. Estimating their evolutions is important for management, command and control structures, and intelligence analysis research. By knowing future agent social and spatial distributions, an analyst can identify emergent leaders, hot spots, and organizational vulnerabilities. Historically, such estimations have depended heavily on qualitative data analyses by subject-matter experts. A few researchers approached the issue using multiagent models and simulation. The models addressed the complex nature of the organization and task assignments, resource distributions, or agent locations. The simulations addressed the near-term organizational changes. This research came from two perspectives: the effects of change in the social network and the effects of geospatial change. Both perspectives can project aspects of emerging organizational structure and future performance, but they can"t examine the interaction between physical and social movements.

关键词： Analytical models Command and control systems Data analysis Data mining Data visualization Intelligent control Intelligent structures Moon Resource management Text analysis coherence and coordination distributed artificial intelligence geospatial change geospatial dimensions multi-agent systems multiagent systems organizational changes social aspects of automation social dimensions social network social networks terrorism terrorist interactions terrorist networks theoretical multiagent model

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Engineering multiuser museum interactives for shared cultural experiences

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ENGINEERING APPLICATIONS OF artificial intelligence 2015年 46卷 180-195页

作者： Confalonieri, Roberto Yee-King, Matthew Hazelden, Katina d'Inverno, Mark de Jonge, Dave Osman, Nardine Sierra, Carles Agmoud, Leila Prade, Henri Artificial Intelligence Res Inst IIIA CSIC Bellaterra Spain Univ London Goldsmiths Coll London England Univ Toulouse 3 Inst Rech Informat Toulouse F-31062 Toulouse France

Multiuser museum interactives are computer systems installed in museums or galleries which allow several visitors to interact together with digital representations of artefacts and information from the museum's collection. In this paper, we describe WeCurate, a socio-technical system that supports cobrowsing across multiple devices and enables groups of users to collaboratively curate a collection of images, through negotiation, collective decision making and voting. The engineering of such a system is challenging since it requires to address several problems such as: distributed workflow control, collective decision making and multiuser synchronous interactions. The system uses a peer-to-peer Electronic Institution (El) to manage and execute a distributed curation workflow and models community interactions into scenes, where users engage in different social activities. Social interactions are enacted by intelligent agents that interface the users participating in the curation workflow with the El infrastructure. The multiagent system supports collective decision making, representing the actions of the users within the El, where the agents advocate and support the desires of their users e.g. aggregating opinions for deciding which images are interesting enough to be discussed, and proposing interactions and resolutions between disagreeing group members. Throughout the paper, we describe the enabling technologies of WeCurate, the peer-to-peer El infrastructure, the agent collective decision making capabilities and the multi-modal interface. We present a system evaluation based on data collected from cultural exhibitions in which WeCurate was used as supporting multiuser interactive. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： distributed artificial intelligence Collective decision making Argumentation Negotiation

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A framework for building cooperative software agents in medical applications

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artificial intelligence IN MEDICINE 1999年第3期16卷 223-249页

作者： Lanzola, G Gatti, L Falasconi, S Stefanelli, M Univ Pavia Dept Informat & Syst Sci Med Informat Lab I-27100 Pavia Italy

Exploiting the information technology may have a great impact on improving cooperation and interoperability among the different professionals taking part to the process of delivering health care services. New paradigms are therefore being devised considering software systems as autonomous agents able to help professionals in accomplishing their duties. To this aim those systems should encapsulate the skills for solving a given set of tasks and possess the social ability to cooperate in order to fetch the required information and knowledge. This paper illustrates a methodology facilitating the development of interoperable intelligent software agents for medical applications and proposes a generic computational model for implementing them. That model may be specialized in order to support all the different information and knowledge related requirements of a Hospital Information System. The architecture is being tested for implementing a prototype system able to coordinate the joint efforts of the professionals involved in managing patients affected by Acute Myeloid Leukemia. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： distributed artificial intelligence multi-agent systems cooperating knowledge based systems distributed health care hospital information systems

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Simulation modeling framework for uncovering system behaviors in the biofuels supply chain network

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SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL 2014年第9期90卷 1103-1116页

作者： Agusdinata, Datu B. Lee, Seokcheon Zhao, Fu Thissen, Wil No Illinois Univ Dept Ind & Syst Engn De Kalb IL 60115 USA No Illinois Univ Environm Sustainabil & Energy Inst De Kalb IL 60115 USA Purdue Univ Sch Ind Engn W Lafayette IN 47907 USA Purdue Univ Sch Mech Engn W Lafayette IN 47907 USA Purdue Univ Div Environm & Ecol Engn W Lafayette IN 47907 USA Delft Univ Technol Fac Technol Policy & Management NL-2600 AA Delft Netherlands

A full realization of alternative energy such as biofuels depends on the existence of a viable supply chain (SC) network. An agent-based simulation approach is pursued to understand the dynamics of the biofuels SC network. The interests of three SC actors are represented: users, biorefineries, and farmers. Each actor type has a binary decision option: adoption or non-adoption of biofuels. This SC network model is characterized by distributed control, time asynchrony, and resource contention among actors, who make decisions based on incomplete knowledge and delayed information. The decision dynamics of these actors are modeled using a computational ecosystem construct. A preliminary set of coupled payoff function for each actor type and each decision is developed to represent interdependencies among SC actors. The simulation model was used to evaluate three archetypes of subsidy policy. The SC network behavior is observed in terms of fraction of actors adopting the biofuel option. The SC network shows behaviors ranging from fixed point equilibrium under no delay and perfect knowledge to periodic and chaotic oscillations. The network behavior is very sensitive to the time delay parameter that partly influences the quality of information on which actors' decisions are based. Several regions of SC behavior are identified. In particular, a chaotic behavior was observed. The work provides a methodological basis for further development, including identification of policies to control undesirable system behaviors.

关键词： distributed artificial intelligence agent-based simulation model biofuels supply chain network

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PeMMAS: A Tool for Studying the Performance of Multiagent Systems Developed in JADE

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IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS 2014年第2期44卷 180-189页

作者： Carrasco, Alejandro Dolores Hernandez, Ma del Carmen Romero-Ternero, Ma Sivianes, Francisco Oviedo, David Ignacio Escudero, Jose Univ Seville Sch Comp Engn Dept Tecnol Elect Seville 41004 Spain

This paper describes the performance measurement for multiagent systems (PeMMAS) tool, a system designed to study and measure the performance of any multiagent system (MAS) developed in JADE. The tool itself is another MAS which is deployed and coexists alongside the one being studied. This characteristic allows us to adapt PeMMAS to any scenario in which MAS deployment in JADE is used. PeMMAS extracts information from the target MAS regarding the use of system resources, the flight time for comprehensive messages according to agent type, as well as the processing time for actions. After processing this information, PeMMAS sends a report to the final user for subsequent analysis.

关键词： distributed artificial intelligence multiagent systems (MAS) performance systems telecontrol

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Multiagent System to Simulate Risk-Allocation and Cost-Sharing Processes in Construction Projects

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JOURNAL OF COMPUTING IN CIVIL ENGINEERING 2013年第3期27卷 307-319页

作者： Karakas, Kivanc Dikmen, Irem Birgonul, M. Talat Middle E Tech Univ Dept Civil Engn TR-06800 Ankara Turkey

Multiagent systems (MASs) consist of several autonomous entities, called agents, that interact with each other to either fulfill their own interests (competition) or reach a common goal (cooperation). In MASs, negotiation is the key form of interaction that enables groups of agents to arrive at a mutual agreement regarding some belief, goal, or plan. The aim of this study is to develop a MAS that simulates the negotiation process between parties (mainly contractor and client) about risk allocation and sharing of cost overruns in construction projects. The MAS was developed using three different negotiation protocols: time-dependent concession, Zeuthen's strategy, and Zeuthen's strategy with Bayesian learning. Sensitivity analysis was carried out to test the effect of reservation value, first-offer value, and negotiation protocol on the settlement amounts. The model was also tested on three hypothetical cases. Results show that it is mainly the reservation value that determines the settlement amount of the negotiation. The developed system can be used by decision makers to understand how the risks and associated costs are shared between parties under different scenarios. DOI: 10.1061/(ASCE)CP.1943-5487.0000218. (C) 2013 American Society of Civil Engineers.

关键词： Construction management Claim negotiations Computer-aided simulation distributed artificial intelligence Multiagent systems Fuzzy sets Bayesian analysis

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CLONE: Collaborative Learning on the Edges

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IEEE INTERNET OF THINGS JOURNAL 2021年第13期8卷 10222-10236页

作者： Lu, Sidi Yao, Yongtao Shi, Weisong Wayne State Univ Dept Comp Sci Detroit MI 48202 USA

The proliferation of edge computing technologies has boosted the development of new applications for a plethora of edge devices. However, many applications face privacy issues and bandwidth limitations. To solve these limitations, we propose a collaborative learning framework on the edges, named CLONE, which is steered by the real-world data sets collected from a large electric vehicle (EV) company and a grocery store of a shopping mall, respectively. We categorize two application scenarios for CLONE, i.e., CLONE in the training stage (CLONE_training) and CLONE in the inference stage (CLONE_inference). As to CLONE_training, we choose the failure prediction of EV battery and associated components as the first use case. While as for CLONE_inference, customer tracking in a grocery store is selected as another case study. In this work, the goal of the CLONE is to support real-time training and inference for connected vehicles and marketing intelligence services. Our experimental results on the EV data show that CLONE is able to reduce model training time without sacrificing algorithm performance. Furthermore, the experimental results on the video data from the grocery store reveal that CLONE is a useful approach to solve the multitarget multicamera tracking problem in a collaborative fashion.

关键词： Cloning Training Batteries Cloud computing Hardware Collaboration Measurement Collaborative learning distributed artificial intelligence edge computing electric vehicle (EV) battery failure prediction multitarget multicamera tracking (MTMCT)

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