Modeling Socio-technical Systems with AgentSpring

AgentSpring is a new agent-based modeling framework especially suited to model and simulate complex socio-technical systems, such as energy markets or transport infrastructures. Common problems encountered when modeling and analyzing such systems are how to represent the variety of facts that describe the system and how to allow agents to make decisions based on those loosely related pieces of information. AgentSpring proposes a solution to these problems by modeling the systems as graphs consisting of agents, artifacts and relations between them. A graph is one of the most flexible data structures, and is made of vertices and edges that connect them. Agents use sophisticated queries to reason over and traverse the graph data structure and make decisions based on the results they discover. They continuously update the graph to include the effects of the decisions they have made. AgentSpring represents the simulated system as a constantly evolving graph of interconnected facts that can transparently be observed and queried in real time by both agents in the model, and the modeler. In addition, AgentSpring allows for the composition of agent behavior modules, where sophisticated behavior can be produced by combining simpler decision making rules. The modeler can easily create a number of heterogeneous agents by combining these behavioral "lego" bricks. Finally, AgentSpring is open-source and is continuously developed based on the feature requests and contributions of the modeler community.Infrastructures, Systems and ServicesTechnology, Policy and Managemen

Agent-based models for policy makers

In order to support policy decisions, we have developed a modelling platform called AgentSpring, which facilitates the development of agent-based models in a modular and structured manner, using state-of-the-art IT development principles and tools. An attractive web-based interface allows for the interaction with policy makers. A model named d13n was developed on the topic of decarbonization of the power generation sector. For this model, relevant applications for policy makers – CO2 reduction, cross-border effects of policies, security of supply – have been identified. Each of those questions can be tackled by developing specific scenarios within the same modelling platform and with the same model core.Infrastructures, Systems and ServicesTechnology, Policy and Managemen

New Methods for Analysis of Systems-of-Systems and Policy: The Power of Systems Theory, Crowd Sourcing and Data Management

Our world is a complex socio-technical system-of-systems (Chappin & Dijkema, 2007; Nikolic, 2009). Embedded within the geological, chemical and biological planetary context, the physical infrastructures, such as power grids or transport networks span the globe with energy and material flows. Social networks in the form of global commerce and the Internet blanket the planet in information flows. While parts of these global social and technical systems have been consciously engineered and managed, the overall system-of-systems (SoS) is emergent: it has no central coordinator or manager. The emergence of this socio-technical SoS has not been without consequences: the human species is currently facing a series of global challenges, such as resource depletion, environmental pollution and climate change. Tackling these issues requires active policy and management of those socio-technical SoS. But how are we to design policies if policy makers and managers have a limited span of control over small parts of the global system of systems?Infrastructures, Systems and ServicesTechnology, Policy and Managemen