Principles of component-based design of intelligent agents

Brazier, Frances M. T.; Jonker, Catholijn M.; Treur, Jan

doi:10.1016/s0169-023x(01)00058-1

Cited by 90 publications

(84 citation statements)

References 26 publications

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“…The multi-agent system and its agents have been specified using the componentbased agent design method DESIRE [1,2,3], and in particular the generic agent model GAM [4]. In each cell in Table 1 the name of an information type [3] is indicated.…”

Section: Fig 1 Overview Of the Multi-agent Systemmentioning

confidence: 99%

“…In each cell in Table 1 the name of an information type [3] is indicated. These information types include generic concepts for communication, observation and action performance from GAM; see [4].…”

Section: Fig 1 Overview Of the Multi-agent Systemmentioning

confidence: 99%

“…[2,3]. Section 3 discusses domain knowledge needed to make such agents realistic, and in Section 4 simulation results are discussed.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Configurations for Photovoltaic Solar Energy Production Using Agent-Based Simulation

Treur

2013

Multiagent System Technologies

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Abstract. To configure a photovoltaic solar energy production plant the circumstances of a site play an important role. A site usually consists a number of specific locations that can be considered ideal (no shadow, perfect southward position, optimal vertical angle). However, much more often locations in a site are not ideal, to an extent that both depends on time of the year and time of the day. An important issue for decision making then is how much loss in efficiency a specific location will entail. In this paper this is analysed by an agent-based simulation method. Here photovoltaic modules with microinverters are conceptualised as autonomous energy producing agents, which are monitored by a central monitoring agent which also interacts with a user via a local and a global Web-based interface agent. The presented approach provides an analysis of the different locations at a site by simulating the agents over one full year with time steps of half an hour per day. The outcome of such a simulation provides an overview of the loss of efficiency for each of the locations depending on its characteristics with respect to shadow, orientation and vertical angle.

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Section: Fig 1 Overview Of the Multi-agent Systemmentioning

confidence: 99%

Section: Fig 1 Overview Of the Multi-agent Systemmentioning

confidence: 99%

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Analysis of Configurations for Photovoltaic Solar Energy Production Using Agent-Based Simulation

Treur

2013

Multiagent System Technologies

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“…[3]. The highest level of abstraction consists of the agents representing the balls (called ball_A, ball_B, and so on) and the External World.…”

Section: Top Levelmentioning

confidence: 99%

“…The composition of the agents is based on the generic agent model as described in [3]. In the current model, four of the generic agent components are used, namely Own Process Control, World Interaction Management, Maintenance of Agent Information, and Agent Specific Task.…”

Section: Agent Levelmentioning

confidence: 99%

The Distributed Weighing Problem: A Lesson in Cooperation Without Communication

Bosse

Hoogendoorn

Jonker

2005

Multiagent System Technologies

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Abstract. Cooperative problem solving without communication is an oftenstudied field within multi-agent research. Realistic problems investigated in this particular field are complex and difficult to model, and therefore not suitable for education. This paper presents the distributed weighing problem as a novel problem to be used for educational purposes within the domain of cooperation without communication. An example agent-based architecture is developed of which parts can be provided to students as a starting-point for practical exercises in cooperative problem solving without communication. Two example strategies are discussed and implemented using this example architecture. Moreover, it is shown how such strategies can be tested and formally validated against a number of desired properties. The educational benefits of the distributed weighing problem are presented as observed in a course for 6 groups of each 3 students.

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Formal semantics of meta-level architectures: Dynamic control of reasoning

Treur

2002

Int. J. Intell. Syst.

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Meta-level architectures for dynamic control of reasoning processes are quite powerful. In the literature many applications in reasoning systems modelling complex tasks are described, usually in a procedural manner. In this paper we present a semantic framework based on temporal partial logic to describe the dynamics of reasoning behaviour. Using these models the semantics of the behaviour of the whole (meta-level) reasoning system can be described by a set of (intended) temporal models.

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Principles of component-based design of intelligent agents

Cited by 90 publications

References 26 publications

Analysis of Configurations for Photovoltaic Solar Energy Production Using Agent-Based Simulation

Analysis of Configurations for Photovoltaic Solar Energy Production Using Agent-Based Simulation

The Distributed Weighing Problem: A Lesson in Cooperation Without Communication

Formal semantics of meta-level architectures: Dynamic control of reasoning

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