Agent-Based Modeling and Simulation of Biological Systems

Agent-based modeling and simulation is a powerful technique in simulating and exploring phenomena that includes a large set of active components represented by agents. The agents are actors operating in a real system, influencing the simulated environment and influenced by the simulated environment. The agents are included in the simulation model as model components performing actions autonomously and interacting with other agents and the simulated environment to represent behaviors in the real system. In this chapter, we describe how to develop an agent-based model and simulation for biological systems in Repast Simphony platform, which is a Java-based modeling system. Repast Simphony helps developers to create a scenario tree including displays of agents, grid and continuous space, data sets, data loaders, histogram, and time charts. At the end of this chapter, we present case studies developed by our research group with references to demonstrate local behavior of biological system

Sensitivity analysis of Repast computational ecology models with R/Repast

Computational ecology is an emerging interdisciplinary discipline founded mainly on modeling and simulation methods for studying ecological systems. Among the existing modeling formalisms, the individual-based modeling is particularly well suited for capturing the complex temporal and spatial dynamics as well as the nonlinearities arising in ecosystems, communities, or populations due to individual variability. In addition, being a bottom-up approach, it is useful for providing new insights on the local mechanisms which are generating some observed global dynamics. Of course, no conclusions about model results could be taken seriously if they are based on a single model execution and they are not analyzed carefully. Therefore, a sound methodology should always be used for underpinning the interpretation of model results. The sensitivity analysis is a methodology for quantitatively assessing the effect of input uncertainty in the simulation output which should be incorporated compulsorily to every work based on in-silico experimental setup. In this article, we present R/Repast a GNU R package for running and analyzing Repast Simphony models accompanied by two worked examples on how to perform global sensitivity analysis and how to interpret the results

Sensitivity analysis of Repast computational ecology models with R/Repast

Computational ecology is an emerging interdisciplinary discipline founded mainly on modeling and simulation methods for studying ecological systems. Among the existing modeling formalisms, the individual-based modeling is particularly well suited for capturing the complex temporal and spatial dynamics as well as the nonlinearities arising in ecosystems, communities or populations due to individual variability. In addition, being a bottom up approach, it is useful for providing new insights on the local mechanisms which are generating some observed global dynamics. Of course no conclusions about model results could be taken seriously if they are based on a single model execution and they are not analyzed carefully. Therefore, a sound methodology should always be used for underpinning the interpretation of model results. The sensitivity analysis is a methodology for quantitatively assessing the effect of input uncertainty in the simulation output which should be incorporated compulsorily to every work based on in silico experimental setup. In this paper we present R/Repast a GNU R package for running and analyzing Repast Simphony models accompanied by two worked examples on how to perform global sensitivity analysis and how to interpret the results

Agent based modelling : initial assessment for use on soil bioaccessibility

This report describes the testing of Agent Based Modelling implementations in three different software packages: Repast-simphony, NetLogo and Insight-maker. These software have been evaluated against their capability to simulate the exposure of people as agents moving across Arsenic contaminated soils. Two of the three tested software (Repast-simphony and NetLogo) are recommended for assessment on more complex problems. An outline work plan is presented for future work

Tools of the Trade: A Survey of Various Agent Based Modeling Platforms

Agent Based Modeling (ABM) toolkits are as diverse as the community of people who use them. With so many toolkits available, the choice of which one is best suited for a project is left to word of mouth, past experiences in using particular toolkits and toolkit publicity. This is especially troublesome for projects that require specialization. Rather than using toolkits that are the most publicized but are designed for general projects, using this paper, one will be able to choose a toolkit that already exists and that may be built especially for one's particular domain and specialized needs. In this paper, we examine the entire continuum of agent based toolkits. We characterize each based on 5 important characteristics users consider when choosing a toolkit, and then we categorize the characteristics into user-friendly taxonomies that aid in rapid indexing and easy reference.Agent Based Modeling, Individual Based Model, Multi Agent Systems

Do Groups Matter? An Agent-based Modeling Approach to Pedestrian Egress

Festivals in city parks attended by individuals and families are a universal feature of urban life. These venues often have the common attributes of vendors and other obstacles that restrict pedestrian movement through certain areas, as well as fixed number of exits. In this study, the authors build an agent-based model (ABM) that incorporates group cohesion forces into this type of pedestrian egress scenario. The scenario considered was an evacuation of 500 people through a single exit. This allowed an investigation into the use of two different simulated pedestrian\u27s heading updating rules

Deploying self-organisation to improve task execution in a multi-agent systems

This paper discusses how the performance of a network of agents can be improved using a self-organisation technique. The multi-agent network performance can be improved by organizing the agents in clusters. Furthermore, principles of self-organisation can be used to create agent organisations triggered when some of the agents have high load. Hence, busy agents within the network may decide to create an organisation to receive extra support from other less busy agents in order to execute more tasks. The paper presents a simulation based on Repast Simphony that has been used to develop the proposed model and describes a set of experiments showing the performance of the system with and without the self-organisation technique