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

ODD Updated

An update to Volker Grimm and colleagues\' Overview, Design concepts and Details (ODD) protocol for documenting individual and agent based models (I/ABM) has recently been published in Ecological Modelling. This renames the \'State variables and scales\' element to \'Entities, state variables and scales\', and the \'Input\' element to \'Input data\', introduces two new Design concepts (\'Basic principles\' and \'Learning\'), and renames another (\'Fitness\' is now generalised to \'Objectives\'). The Design concepts element can now also be shortened such that it is not required to include any design concept that is irrelevant to the model, and expanded to include new design concepts more appropriate to the model being described. Other clarifications of intentions in the original protocol have been made.ODD, Individual Based Models, Agent Based Models, Replication, Documentation

Overview on agent-based social modelling and the use of formal languages

Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft

Business Ecosystem and Stakeholders’ Role Transformation: Evidence from China’s Emerging Electric Vehicle Industry

Nurturing an emerging industry’s business ecosystem always requires stakeholders’ efforts and role transformation. By systematically reviewing and studying the evolution of the Chinese electric vehicle industry, this paper constructs a three-dimensional theoretical framework including stages of business ecosystem lifecycle, stakeholder classification and functional roles, to analyse the transformation both of different stakeholders and their functional roles. The findings show that business ecosystem stakeholders have experienced role transformation following a mechanism defined as the ‘Triple Oscillation’ Model during the evolution of the emerging industry. These findings also help develop a conceptual model of agent-based system for business ecosystem evolution, which could be a starting point for further emerging industry study

Accelerating social science knowledge production with the coordinated open-source model

With the growing complexity of knowledge production, social science must accelerate and open up to maintain explanatory power and responsiveness. This requires redesigning the front-end of research to build an open and expandable knowledge infrastructure that stimulates broad collaborations, enables breaking down inertia and path dependencies of conventional approaches, and boosts discovery and innovation. This article discusses the coordinated open-source model as a promising organisational scheme that can supplement conventional research infrastructure in certain areas. The model offers flexibility, decentralization, and community-based development and aligns with open science ideas, such as reproducibility and transparency. Similar solutions have been successfully applied in natural science, but social science lags behind. I present the model's design, and consider its potential and limitations (e.g., regarding development, sustainability and coordination). I also discuss open-source applications in various areas, including the first open-source survey harmonization project in social science

Enabling collaborative numerical modeling in earth sciences using knowledge infrastructure

Knowledge Infrastructure is an intellectual framework for creating, sharing, and distributing knowledge. In this paper, we use Knowledge Infrastructure to address common barriers to entry to numerical modeling in Earth sciences: computational modeling education, replicating published model results, and reusing published models to extend research. We outline six critical functional requirements: 1) workflows designed for new users; 2) a community-supported collaborative web platform; 3) distributed data storage; 4) a software environment; 5) a personalized cloud-based high-performance computing platform; and 6) a standardized open source modeling framework. Our methods meet these functional requirements by providing three interactive computational narratives for hands-on, problem-based research demonstrating how to use Landlab on HydroShare. Landlab is an open-source toolkit for building, coupling, and exploring two-dimensional numerical models. HydroShare is an online collaborative environment for the sharing of data and models. We describe the methods we are using to accelerate knowledge development by providing a suite of modular and interoperable process components that allows students, domain experts, collaborators, researchers, and sponsors to learn by exploring shared data and modeling resources. The system is designed to support uses on the continuum from fully-developed modeling applications to prototyping research software tools

Crossing the chasm: a 'tube-map' for agent-based social simulation of policy scenarios in spatially-distributed systems

Agent based models (ABMs) simulate actions and interactions of autonomous agents/groups and their effect on systems as a whole, accounting for learning without assuming perfect rationality or complete knowledge. ABMs are an increasingly popular approach to studying complex, spatially distributed socio-environmental systems, but have still to become an established approach in the sense of being one that is expected by those wanting to explore scenarios in such systems. Partly, this is an issue of awareness – ABM is still new enough that many people have not heard of it; partly, it is an issue of confidence – ABM has more to do to prove itself if it is to become a preferred method. This paper will identify advances in the craft and deployment of ABM needed if ABM is to become an accepted part of mainstream science for policy or stakeholders. The conduct of ABM has, over the last decade, seen a transition from using abstracted representations of systems (supporting theory-led thought experiments) to more accessible representations derived empirically (to deliver more applied analysis). This has enhanced the perception of potential users of ABM outputs that the latter are salient and credible. Empirical ABM is not, however, a panacea, as it demands more computing and data resources, limiting applications to domains where data exist along with suitable environmental models where these are required. Further, empirical ABM is still facing serious questions of validation and the ontology used to describe the system in the first place. Using Geoffrey A. Moore’s Crossing the Chasm as a lens, we argue that the way ahead for ABM lies in identifying the niches in which it can best demonstrate its advantages, working with collaborators to demonstrate that it can deliver on its promises. This leads us to identify several areas where work is needed