Agent Based Modeling and Simulation: An Informatics Perspective

The term computer simulation is related to the usage of a computational model in order to improve the understanding of a system's behavior and/or to evaluate strategies for its operation, in explanatory or predictive schemes. There are cases in which practical or ethical reasons make it impossible to realize direct observations: in these cases, the possibility of realizing 'in-machina' experiments may represent the only way to study, analyze and evaluate models of those realities. Different situations and systems are characterized by the presence of autonomous entities whose local behaviors (actions and interactions) determine the evolution of the overall system; agent-based models are particularly suited to support the definition of models of such systems, but also to support the design and implementation of simulators. Agent-Based models and Multi-Agent Systems (MAS) have been adopted to simulate very different kinds of complex systems, from the simulation of socio-economic systems to the elaboration of scenarios for logistics optimization, from biological systems to urban planning. This paper discusses the specific aspects of this approach to modeling and simulation from the perspective of Informatics, describing the typical elements of an agent-based simulation model and the relevant research.Multi-Agent Systems, Agent-Based Modeling and Simulation

A methodological framework for the analysis of agent-based supply chain planning simulations

Agent-based simulation is considered a promising approach for supply chain (SC) planning, configuration and design. Although there have been many important advances on how to specify, design, and implement agent-based simulation, the concerned literature does not properly addresses the analysis phase. In this early phase, SC stakeholders decide what kind of simulation experiments should be performed and their requirements, which considerably influence the whole development process and the resulting simulation environment. This work proposes an agent-based simulation framework for modeling SC systems in the analysis phase. In addition, it proposes a formal method for converting the analysis model into specification and design models. The proposed framework is being validated by means of an agent-based simulation platform developed in the context of the lumber industry.

Theory of deferred action: Agent-based simulation model for designing complex adaptive systems

Deferred action is the axiom that agents act in emergent organisation to achieve predetermined goals. Enabling deferred action in designed artificial complex adaptive systems like business organisations and IS is problematical. Emergence is an intractable problem for designers because it cannot be predicted. We develop proof-of-concept, conceptual proto-agent model, of emergent organisation and emergent IS to understand better design principles to enable deferred action as a mechanism for coping with emergence in artefacts. We focus on understanding the effect of emergence when designing artificial complex adaptive systems by developing an exploratory proto-agent model and evaluate its suitability for implementation as agent-based simulation

A modular hybrid simulation framework for complex manufacturing system design

For complex manufacturing systems, the current hybrid Agent-Based Modelling and Discrete Event Simulation (ABM–DES) frameworks are limited to component and system levels of representation and present a degree of static complexity to study optimal resource planning. To address these limitations, a modular hybrid simulation framework for complex manufacturing system design is presented. A manufacturing system with highly regulated and manual handling processes, composed of multiple repeating modules, is considered. In this framework, the concept of modular hybrid ABM–DES technique is introduced to demonstrate a novel simulation method using a dynamic system of parallel multi-agent discrete events. In this context, to create a modular model, the stochastic finite dynamical system is extended to allow the description of discrete event states inside the agent for manufacturing repeating modules (meso level). Moreover, dynamic complexity regarding uncertain processing time and resources is considered. This framework guides the user step-by-step through the system design and modular hybrid model. A real case study in the cell and gene therapy industry is conducted to test the validity of the framework. The simulation results are compared against the data from the studied case; excellent agreement with 1.038% error margin is found in terms of the company performance. The optimal resource planning and the uncertainty of the processing time for manufacturing phases (exo level), in the presence of dynamic complexity is calculated

Predictive Agent-Based Crowd Model Design Using Decentralized Control Systems

As a complex system, crowd dynamics emerge bottom-up from the local interactions between pedestrians as component subsystems. This article proposes a predictive agent-based crowd simulation model to analyze the outcomes of emergency evacuation scenarios taking into account collisions between pedestrians, smoke, fire sprinklers, and exit indicators. The crowd model is based on a decentralized control system structure, where each pedestrian agent is governed through a deliberative-reactive control architecture. The simulation model for evacuation includes a routing-based control system for dynamic-guided evacuation. A design case illustrates the modeling process. Results show that the crowd simulation model based on agent autonomy and local interactions is able to generate higher level crowd dynamics through emergence.publishedVersio

PERAMALAN PERMINTAAN SUKU CADANG OTOMOTIF KARET DENGAN INTEGRASI AGENT BASED MODELLING DAN DOUBLE EXPONENTIAL SMOOTHING

The objective of this study was to design an agent model for forecasting demand for rubber-based automotive parts using the Agent Based Modelling and Double Exponential Smoothing (ABMDES) approach.  Model design in rubber-based automotive spare parts forecasting using the integration of Agent Based Modelling (ABM) approach and Double Exponential Smoothing (DES) technique was done using agent design approach based on class diagram and definition function for each agent in mathematics models including DES-based forecasting. The ABM design has a structure consisting of an agent ID, an attribute to be calculated by the computer and function / process consisting of a function that has values ​​and voids (unstructured). Combining ABM and DES can guide us to see the forecast accuracy, monitoring the estimation of stock shortage and the excess of stock due to errors in DES forecast. Therefore, the Agent Based Modelling-Double Exponential Smoothing (ABMDES) approach is suitable for modelling the demand of rubber-based automotive parts in business simulation. Keywords: double exponential smoothing, function, SMEs, shortag

Simulation Modelling in Healthcare: Challenges and Trends

AbstractIn this paper, we describe simulation models in healthcare that have been developed in the past two decades. Simulation systems, ranging from simulation of patient flow in emergency rooms to simulation of populations with a specific chronic diseases, are reviewed. Simulation types included discrete event simulation (DES) and agent based simulation (ABS). A trend of variability and scalability were identified, and discussed in terms of platform used to develop the model, data sources, and computational power needed to run the simulation. In the synthesis of simulation models, programming languages and products emerged as clusters. Design models and systems engineering development processes are examined with a focus on requirements discovery, models and scenarios of simulation. Graphic user interfaces in the simulation tools in healthcare are reviewed in terms of visual design and human factors. Furthermore, interaction modes and trends of information visualization techniques used for the simulations are reported. Agent-based simulation models in particular were reviewed, and findings suggest agent characteristics varied across literature researched in aspects such as socio-demographic design considerations