Towards a Community Framework for Agent-Based Modelling

Agent-based modelling has become an increasingly important tool for scholars studying social and social-ecological systems, but there are no community standards on describing, implementing, testing and teaching these tools. This paper reports on the establishment of the Open Agent-Based Modelling Consortium, www.openabm.org, a community effort to foster the agent-based modelling development, communication, and dissemination for research, practice and education.Replication, Documentation Protocol, Software Development, Standardization, Test Beds, Education, Primitives

Agent-based modelling of air transport demand

Constraints such as opening hours or passenger capacities influence travel options that can be offered by an airport and by the connecting airlines. If infrastructure, policy or technological measures modify transport options, then the benefits do not only depend on the technology, but also on possibly heterogeneous user preferences such as desired arrival times or on the availability of alternative travel modes. This paper proposes an agent-based, iterative assignment procedure to model European air traffic and German passenger demand on a microscopic level, capturing individual passenger preferences. Air transport technology is simulated microscopically, i.e. each aircraft is represented as single unit with attached attributes such as departure time, flight duration or seat availability. Trip-chaining and delay propagation can be added. Microsimulation is used to verify and assess passengers’ choices of travel alternatives, where those choices improve over iterations until an agent-based stochastic user equilibrium is reached. This requires fast simulation models, thus, similar to other approaches in air traffic modelling a queue model is used. In contrast to those approaches, the queue model in this work is solved algorithmically. Overall, the approach is suited to analyze, forecast and evaluate the consequences of mid-distance transport measures

Agent-based modelling - A methodology for the analysis of qualitative development processes

The tremendous development of an easy access to computational power within the last 30 years has led to the widespread use of numerical approaches in almost all scientific disciplines. The first generation of simulation models was rather focused on stylized empirical phenomena. With agent-based modelling, however, the trade-off between simplicity in modelling and taking into account the complexity of the socio-economic reality has been enhanced to a large extent. This paper serves as a basic instruction on how to model qualitative change using an agent-based modelling procedure. The necessity to focus on qualitative change is discussed, agent-based modelling is explained and finally an example is given to show the basic simplicity in modelling.agent-based modelling, methodology, evolutionary economics, qualitative change

Errors and Artefacts in Agent-Based Modelling

The objectives of this paper are to define and classify different types of errors and artefacts that can appear in the process of developing an agent-based model, and to propose activities aimed at avoiding them during the model construction and testing phases. To do this in a structured way, we review the main concepts of the process of developing such a model – establishing a general framework that summarises the process of designing, implementing, and using agent-based models. Within this framework we identify the various stages where different types of errors and artefacts may appear. Finally we propose activities that could be used to detect (and hence eliminate) each type of error or artefact.Verification, Replication, Artefact, Error, Agent-Based Modelling, Modelling Roles

Agent-Based Modelling: The Next 15 Years

This short note makes recommendations for the future direction of research in agent-based modelling (ABM). It is a personal view based on my experience as a policy adviser who has recently come to ABM. I suggest that to promote the use of ABM, the ABM community needs demonstrate the value of modelling to other social scientists by showing-by-doing and offering training projects; and to produce tools, guidance on good-practice and basic building blocks. Then the policy contexts most likely to benefit from ABM need to be identified along with any new data requirements, so that the usefulness of ABM can be demonstrated to policy analysts. This is, in my view, the challenge facing the ABM community for the next 15 years.Agent-Based Modelling,, NetLogo, Policy Advice

Spatial agent-based modelling

Archaeologists were among some of the earliest users of agent-based modelling, but recent years have undoubtedly seen a surge of interest in the use of this technique to infer past behaviour or help develop new theories and methods. Although ABM software is much easier to use than it was even 20 years ago and sufficiently powerful computers are more readily available, the success of a modelling project is still largely determined by decisions made about the purpose and design of the model, and the subsequent experimental regime. This chapter guides the reader through those key issues. It covers epistemological topics such as the role of the model in a wider project, the trade-off between realism and generality, the idea of generative modelling and the importance of adequate experimentation. It also discusses technical issues such as options for the integration of ABM and GIS, and even the dangers inherent in poor design decisions about the scheduling of agent behaviour

Chemical industry supply chain optimisation using agent-based modelling

In this paper we present an application of Supply Chain Spread Sheet Simulator (SCSS) in a task dealing with chemical industry supply chain redesign and optimisation. SCSS uses principles of Agent-Based Modelling combining 4 types of agents with 3 algorithms to control their behaviour. Location Algorithm is used to place the logistics objects satisfying the demand of customers, Clarke&Wright's Savings Algorithm is applied to plan the routes and Past Stock Movement Simulation is used to control the stock levels. SCSS is developed in MS Excel using programming language Visual Basic for Applications. Its basic functionality is discussed simulating a real task dealing with the redesign of the distribution system for goods coming from chemical industry in the Czech Republic. We test 6 different structures of the distribution system differing in number of located logistics objects ranging from 1 to 6. Based on the outputs of SCSS recalculated to distribution costs we suggest decreasing the number of located warehouses from 6 to 1 estimating almost 33 % distribution costs savings per year

Reply to Will and Hegselmann

[No abstract]Replication, Social Dilemmas, Simulation Methodology, Cooperation, Trust, Agent-Based Modelling