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A multi-agent framework for dynamic task assignment and delegation in task distribution

机译:用于任务分配中动态任务分配和委派的多主体框架

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Agent-based systems are deployed in distributed data and control environments where resources usage are claimed to be more efficient. Researches have shown that intelligent agents offer excellent performance in distributed environments influenced by their autonomous or semi-autonomous actions with minimal human intervention. Assigned with roles, these agents are thus viewed as human-like societies that are capable of planning, coordinating, and executing tasks to achieve their goals. In a similar fashion, we model agents in our work based on the peculiarities of human society to achieve optimum performance in a dynamic multi-skills environment. Due to time and task constraints, agents are assigned with multiple roles and perform various other tasks. In this paper, we discuss a framework for dynamic task assignment and delegation in handling multi-task problems for a society of agents to achieve a common goal in allocated time. To test the framework, we adopt and animate the Final Examination Paper Preparation (FEPP) process in a multi-agent system that involves a number of faculty branches where multiple and dynamic task delegations are possible.
机译:基于代理的系统部署在分布式数据和控制环境中,其中据称资源使用效率更高。研究表明,智能代理在受其自主或半自主动作影响的分布式环境中提供了出色的性能,而无需人工干预。这些角色被分配了角色,因此被视为类人社会,能够计划,协调和执行任务以实现其目标。以类似的方式,我们根据人类社会的特殊性在工作中对主体进行建模,以在动态的多技能环境中实现最佳绩效。由于时间和任务的限制,代理被分配了多个角色并执行其他各种任务。在本文中,我们讨论了一个动态任务分配和委派的框架,该框架用于处理多个任务问题,以使代理商社会在分配的时间内实现共同的目标。为了测试该框架,我们采用了多代理系统中的期末试卷准备(FEPP)过程并对其进行动画处理,该系统涉及多个教职部门,可以进行多个动态任务委派。

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