An Overview of Multi-Agent Simulation in Organizations

An Overview of Multi-Agent Simulation in Organizations

Nikola Vlahovic (Faculty of Economics and Business, University of Zagreb, Croatia) and Vlatko Ceric (Faculty of Economics and Business, University of Zagreb, Croatia)
DOI: 10.4018/978-1-4666-5888-2.ch116
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Background

Computer simulation modeling is an established method in scientific and industrial applications, appropriate for obtaining insight into the dynamics of organizations. Modeling is used to represent a part of reality in sufficient detail, and resulting model is an artificial system used for experimentation. There are several situations when replacement of the real system by an artificial one is helpful or even necessary.

  • Inaccessibility of the real world system: Sometimes a part of the real world system that should be studied is not accessible either because the system does not exist any more or is not yet put into operation.

  • Real world system is inappropriate for experimentation: Some real world systems may be affected in undesired way by experimentation. Examining effects of drastic changes in taxing and pricing policies may e.g. disturb the fiscal system, or discourage production and consumption.

  • Time scale or behavior of the system is inappropriate for observation: A number of systems such as investments in some industries generate results over long periods of time, making it hard to collect enough data from the real system for a meaningful analysis. Simulation is using virtual time that can be accelerated or slowed down as needed in order to observe a particular phenomenon.

  • Intensive dynamics of the system: All elements of simulation model can be taken under full control. This is especially important in economics for the purpose of studying the impact of changes in one factor on behavior of the whole system, while holding all other factors at the same level. This presumption cannot be achieved in a real life economic system (e.g. system of supply and demand).

Key Terms in this Chapter

Agent-Based Modeling (ABM): Models of social groups and networks where each member is represented by an individual agent with its own behavior patterns. Collective behaviors emerge as consequence of individual interactions within the group. These models are used in social sciences to study social interactions and emergent social phenomena.

Virtual Time: A time advancement paradigm used to handle the course of events within the simulation model. Event based simulations use event queues that allow the simulation time to advance to the time stamp of the next event. In this way time scale can be stretched or compressed, depending on the needs of the model.

Discrete-Event Simulation: A type of simulation where simulation mechanism advances simulation clock to discrete points in time. Time advancement can be round-based (simulation clock is advanced for a constant number of time units for each round of the simulation) or step-based (simulation clock is advanced to the time stamp of the next event in the event queue).

Experimental Frame: Establishes the set of experiments for which the model is valid. It has to be determined in early stages of model development.

System Dynamics: A continuous simulation of systems exhibiting feedback loops. The feedbacks can either intensify activities of the system (positive feedback) or slow them down and stabilize the system (negative feedback).

Artificial Environment: A model of the environment where the simulation model is operating. Environment model is completely controllable by the modeler. Particular environment models are highly relevant when modeling adaptive elements of the system or when using adaptive capabilities of the agents contained within the model.

Agent-Based Social Simulation (ABSS): Allows for simulating different elements of social systems in form of artificial intelligent agents that are placed in simulated virtual environment in order to observe their behavior and make conclusions about real-life social phenomena.

Multi Agent System: A system consisting of a number of agents that interact with each other through communication, thus allowing them to achieve goals that are beyond their individual capabilities.

Multi Agent Simulation: Another term for agent-based social simulation (ABSS).

Intelligent Software Agent: A system situated within a part of environment that senses this environment and acts on it over time in pursuit of its own agenda.

Simulation Modeling: An established method in science and industry used to map a part of reality in sufficient detail using a model. Developed model should be able to answer questions directed to the real system without disturbing functioning of the real system.

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