Authors:
Lluís Ribas-Xirgo
and
Ismael F. Chaile
Affiliation:
Universitat Autònoma de Barcelona, Spain
Keyword(s):
Agent-Based Modelling; Mixed-Reality Environments; Multi-Agent Systems; Physical Agents.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bioinformatics
;
Biomedical Engineering
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Multi-Agent Systems
;
Operational Research
;
Physical Agents
;
Robot and Multi-Robot Systems
;
Simulation
;
Software Engineering
;
Symbolic Systems
Abstract:
Agent-based modelling enables simulating complex systems and controlling them, as well. In the industrial domain there are plenty of these systems not only because of the size but also because of the need for fault-tolerance and adaptability. Typically, these cases are solved by dividing systems into different dimensions, including the transportation one. In this paper, we take this approach to build a framework to develop and control transportation in applications within the industrial domain, which will be tested on an automated laboratory. The framework is based on a multi-agent simulator that contains the model of the plant with transportation agents having a multi-layered architecture. The lower-level layers correspond to those that would be embedded into physical transportation agents. Therefore, while agents communicate to each other within the simulator environment, communication between upper-level layers and lower-lever layers of each agent is done internally for the simula
ted parts and externally for the real counterparts. The simulator can be used stand-alone to functionally validate a system or in combination with real agents as a monitoring/controlling tool. Preliminary results prove the viability of the framework as a design tool and show the difficulties to work with physical agents.
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