Symbolic discrete-time planning with continuous numeric action parameters for agent-controlled processes

Pantke, Florian; Edelkamp, Stefan; Herzog, Otthein

doi:10.1016/j.mechatronics.2015.06.015

Cited by 3 publications

(1 citation statement)

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“…Self-organizing aspects of agents can reduce the organization complexity significantly and can aid to improve overall system stability of the a for mentioned tasks [7]. Planning tasks of industrial agents, e.g., the co-ordination and scheduling of production resources and supply chains [6], is well matched by the BDI architecture and reflected by the Plans database.…”

Section: The Agent Model Of Computation and Industrial Agentsmentioning

confidence: 99%

Agent-based Solutions for Industrial Environments composed of Autonomous Mobile Agents, Modular Agent Platforms, and Tuple Spaces.

Bosse

2015

Proceedings of 2nd International Electronic Conference on Sensors and Applications

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Design and Production processes become more and more complex. Today, industrial manufacturing environments consists of large-scale networks connecting smart sensors, embedded systems, server, desktop, and mobile computers. Mobile software Agents can be used in such strong heterogeneous environments with design, manufacturing, and logistics facilities. A unified agent model and a agent processing platform can overcome network and system barriers arising in such complex systems. The deployment of Industrial Agents can improve the scalability, productivity, and stability of modern adaptive and customized production processes, and aid the integration of sensor networks in cloud computing. This article shows the deployment and the relationship of industrial agents to industrial environments and common agent models, finally mapped on mobile program code executed by a low-resource and highly portable agent processing platform.

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Section: The Agent Model Of Computation and Industrial Agentsmentioning

confidence: 99%