A Model of BDI-Agent in Game-Theoretic Framework

Ambroszkiewicz, Stanislaw; Komar, Jarosław

doi:10.1007/3-540-46581-2_2

“…This also affects the ART 3 and ART 2 in some cases. Another interesting phenomenon is that for set a, the ARTs are mostly worse for the agents with the suspend-resume mechanism (2,4) than the agents without such mechanism (1,3). It is because in agents 1 and 3, the execution of the tasks is not strictly scheduled according to the policy that the higher-priority tasks get processed first.…”

Section: With Different Ways Of Controlling the Computational Componementioning

confidence: 99%

“…At the end of each iteration step, the intentions are executed. This idea of implementing the BDI agent is adopted in many BDI systems [1,10,19,30]. In PRS, the agent will not proceed to the next step until the current step is finished.…”

Section: Introductionmentioning

confidence: 99%

A general framework for parallel BDI agents in dynamic environments

Zhang¹,

Huang²

2008

Web Intelligence and Agent Systems: An International Journal

5

0

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In this paper, a general framework for the parallel BDI model suitable for dynamic environments is proposed. It is a parallel agent architecture that supports the following agent abilities at architecture level: (1) the ability to monitor the environment at all times and respond to emergencies timely; (2) the ability to reconsider and re-schedule goals, intentions and actions in reaction to unexpected or new information; (3) the ability to perform multiple actions at once; (4) the ability to perceive, deliberate and act simultaneously; (5) the ability to prioritize the deliberations and intention executions. We define the functions and the operations of the processing units in the agent and how these units interact, cooperate and synchronize with each other. With the advances in semiconductor technology which allow multiple processing units to be implemented on the same silicon chip, a parallel BDI agent will be an effective way to enable it to perform in a dynamically changing environment when the arrival rate of events is high. We illustrate the working of a parallel agent under the general framework with an agent simulating the behaviour of a vessel captain navigating in sea. Then the performance of a parallel agent is evaluated against several versions of sequential agents. The issue of how much parallelism and how to configure a parallel agent based on the general framework are studied by experiments with different configurations of the parallel agent.

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“…This also affects the ART 3 and ART 2 in some cases. Another interesting phenomenon is that for set a, the ARTs are mostly worse for the agents with the suspendresume mechanism (2,4) than the agents without such mechanism (1,3). It is because in agents 1 and 3, the execution of the tasks is not strictly scheduled according to the policy that the higher-priority tasks get processed first.…”

Section: With Different Time Resources Allocation In Sequential Agentsmentioning

confidence: 99%

“…At the end of each iteration step, the intentions are executed. This idea of implementing the BDI agent is adopted in many BDI systems [30,1,19,10]. In PRS, the agent will not proceed to the next step until the current step is finished.…”

Section: Introductionmentioning

confidence: 99%

A General Framework for Parallel BDI Agents

Zhang

¹

,

Huang

²

2006

2006 IEEE/WIC/ACM International Conference on Intelligent Agent Technology

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In this paper, a general framework for the parallel BDI model suitable for dynamic environments is proposed. It is a parallel agent architecture that supports the following agent abilities at architecture level: (1) the ability to monitor the environment at all times and respond to emergencies timely; (2) the ability to reconsider and re-schedule goals, intentions and actions in reaction to unexpected or new information; (3) the ability to perform multiple actions at once; (4) the ability to perceive, deliberate and act simultaneously; (5) the ability to prioritize the deliberations and intention executions. We define the functions and the operations of the processing units in the agent and how these units interact, cooperate and synchronize with each other. With the advances in semiconductor technology which allow multiple processing units to be implemented on the same silicon chip, a parallel BDI agent will be an effective way to enable it to perform in a dynamically changing environment when the arrival rate of events is high. We illustrate the working of a parallel agent under the general framework with an agent simulating the behaviour of a vessel captain navigating in sea. Then the performance of a parallel agent is evaluated against several versions of sequential agents. The issue of how much parallelism and how to configure a parallel agent based on the general framework are studied by experiments with different configurations of the parallel agent.

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“…Game theory has also found its position in the formalisation of agent models, e.g. [18]. A great number of formal models of agents have been proposed and investigated in the literature, see e.g.…”

Section: Introductionmentioning

confidence: 99%

Slabs: A Formal Specification Language for Agent-Based Systems

Zhu

¹

2001

Int. J. Soft. Eng. Knowl. Eng.

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Being autonomous, proactive and adaptive, an agent-based system may demonstrate emergent behaviours, which are neither designed by the developers nor expected by the users of the system. Whether or not such emergent behaviours are advantageous, methods for the specification of agent behaviours must be developed to enable software engineers to analyse agent-based systems before they are implemented. This paper presents a formal specification language SLABS for agent-based systems. It is a model-based specification language defined based on the notion of agents as encapsulations of data, operations and behaviours. The behaviour of an agent is defined by a set of rules that describe the action/reaction of the agent in certain environment scenarios. The style and expressiveness of the language is demonstrated by examples like ants, personal assistants and speech-act style of agent communications.

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A Model of BDI-Agent in Game-Theoretic Framework

Cited by 7 publications

References 10 publications

A general framework for parallel BDI agents in dynamic environments

A general framework for parallel BDI agents in dynamic environments

A General Framework for Parallel BDI Agents

Slabs: A Formal Specification Language for Agent-Based Systems

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