Ontology Development and Agent Communication in Agent-Based Simulation of AGVS

Abstract

For effective information exchange in agent-based systems, domain-specific ontology is strongly needed, which is the vocabulary representing facts and relations of objects in the domain. In this paper, a semi-formal domain-specific ontology for shop floor focusing on Automated Guided Vehicle Systems (AGVS) is presented. The domain-specific ontology is developed on Protégé, a leading frame-based ontology editor, and is further converted into JADE™ (Java Agent DEvelopment Framework) compliant java classes. The developed ontology has been used in agent-communication of a simulator known as agent-based shop floor simulator (ABSFSim). Agent communication used in the ABSFSim is discussed. Agentbased simulation model of a sample manufacturing system is built with ABSFSim and the working of the model is verified and validated by comparing the output with an equivalent model developed in ProModel. The ontology development process presented in this paper is useful for developing agent-based models in different sections of manufacturing and also for developing high level agent-based software platforms for manufacturing systems.

Method for elicitation, documentation and validation of software user requirements (MEDoV)

“…Also, for effective information exchange in agent-based systems, domain-specific ontology is strongly needed [17].…”

Simulation of AGV System – A Multi Agent Approach

“…A subset of these ontological classes was used in the communication of the manufacturing agents for simulation of AGV system. For more details of semiformal domain-specific ontology for shop floor focusing on AGVS interested readers may refer to (Komma et al, 2012).…”

Modelling and Simulation on Recycling of Electric Vehicle Batteries – Using Agent Approach

“…Thus, if we want to arrive at a useful contrast between agent and program, we must restrict at least some of the notions of environment, sensing and acting. Meanwhile, domain-specific ontology is needed in Agentbased systems [31].…”

“…An agent is defined as autonomous, computational entities that can be viewed as perceiving its environment through sensors and acting upon their environment through effectors, and a few common properties that can be assigned to an agent are autonomy, cooperativity, reactivity, pro-activeness and learning; Multi Agent is a relatively new specialization of Distributed Artificial Intelligence that helps in developing complex systems with concurrent behaviour [31]. The definition of an agent depends heavily on what we take as the environment, and on what sensing and acting mean.…”

“…The mechanisms consist of 'timeout', 'rate', 'condition', 'message' and 'agent arrival' in AnyLogic, in this paper we adopt 'message'. Agent communication is in the basic ABSFSim (Agent-based shop floor simulator), not the developed one [31,33].…”