The emergence of institutions for the management of the commons

In this paper we present an abstract replication of institutional emergence patterns observed in common pool resource (CPR) problems. We used the ADICO grammar of institutions as the basic structure to model both agents' strategies and institutions. Through an evolutionary process, agents modify their behaviours and eventually establish a management institution for their CPR system, leading to significant benefits both for them and for the commons as a whole. We showed that, even if our model has a high level of abstraction, by taking an evolutionary perspective and using the ADICO structure we are able to observe common institutional patterns. We confirm that institutions do indeed contribute to the sustainable management of common pool resource systems

Exploring the dynamics of the world energy system : an agent-based - system dynamics model

Due to limitation of some energy resources, there are concerns whether the world energy system (WES) can supply sufficient energy for societies in the future. Scientists develop models to gain insights into the system. GEMBA is a system dynamics model developed by Dale to explore the global energy supply using biophysical economics approach. Biophysical economics theory analyzes the economy based on the physical properties and structures of real economic systems and it considers natural resources and their impacts on the economic processes. GEMBA like other system dynamics models adopt a top-down view on the WES. The top-down view assumes that all elements of a system have global knowledge about the system. Many of such models do not capture some characteristics of a WES such as geographical resource distribution and demand diversity. In addition, it is often not possible to analyze the emergent effects from variations in low-level elements on the system behavior in top-down analysis. We developed an exploratory agent-based model, by taking a biophysical economics lens, for bottom-up analysis of a WES and relevant natural resources. We decomposed the world into a number of geographical regions to capture resource distribution and demand diversity in the WES. Our Multi-Region World Energy Model (MRWEM) combines the GEMBA with the concept of energy-return-on-investment (EROI) for imported energy. So, in MRWEM the internal behaviors of the world regions are modeled with GEMBA and the system dynamics approach while the inter-regions behaviors are modeled with agent-based modeling approach. MRWEM exhibits a number of advantages over GEMBA. First, it provides insights on the inter-regions energy movements and trade which is impossible in GEMBA. Second, MRWEM provides flexibility in analysis as changes in the model can be done at the level of regions not the whole world. Also, MRWEM facilitates analysts to analyze the WES using different geographical decompositions. Moreover, it shows that the hybrid adoption of agent-based modeling and system dynamics is possible and insightful when the level of abstraction is very high

Structuring Qualitative Data for Agent-Based Modelling

Using ethnography to build agent-based models may result in more empirically grounded simulations. Our study on innovation practice and culture in the Westland horticulture sector served to explore what information and data from ethnographic analysis could be used in models and how. MAIA, a framework for agent-based model development of social systems, is our starting point for structuring and translating said knowledge into a model. The data that was collected through an ethnographic process served as input to the agent-based model. We also used the theoretical analysis performed on the data to define outcome variables for the simulation. We conclude by proposing an initial methodology that describes the use of ethnography in modelling

Advances in Computational Social Science and Social Simulation

Aquesta conferència és la celebració conjunta de la "10th Artificial Economics Conference AE", la "10th Conference of the European Social Simulation Association ESSA" i la "1st Simulating the Past to Understand Human History SPUHH".Conferència organitzada pel Laboratory for Socio­-Historical Dynamics Simulation (LSDS-­UAB) de la Universitat Autònoma de Barcelona.Readers will find results of recent research on computational social science and social simulation economics, management, sociology,and history written by leading experts in the field. SOCIAL SIMULATION (former ESSA) conferences constitute annual events which serve as an international platform for the exchange of ideas and discussion of cutting edge research in the field of social simulations, both from the theoretical as well as applied perspective, and the 2014 edition benefits from the cross-fertilization of three different research communities into one single event. The volume consists of 122 articles, corresponding to most of the contributions to the conferences, in three different formats: short abstracts (presentation of work-in-progress research), posters (presentation of models and results), and full papers (presentation of social simulation research including results and discussion). The compilation is completed with indexing lists to help finding articles by title, author and thematic content. We are convinced that this book will serve interested readers as a useful compendium which presents in a nutshell the most recent advances at the frontiers of computational social sciences and social simulation researc

The emergence of institutions for the management of the commons

In this paper we present an abstract replication of institutional emergence patterns observed in common pool resource (CPR) problems. We used the ADICO grammar of institutions as the basic structure to model both agents' strategies and institutions. Through an evolutionary process, agents modify their behaviours and eventually establish a management institution for their CPR system, leading to significant benefits both for them and for the commons as a whole. We showed that, even if our model has a high level of abstraction, by taking an evolutionary perspective and using the ADICO structure we are able to observe common institutional patterns. We confirm that institutions do indeed contribute to the sustainable management of common pool resource systems

Structuring Socio-Technical Complexity in Infrastructure Systems: The Biogas System

Abstract: Infrastructure systems consist of many heterogeneous decision making entities and technological artefacts. They are governed through public policy that unravels in a multi-scale institutional context, ranging from norms and values to technical standards. For example, to integrate biogas infrastructure in a region, various forms of governance, laws and regulations need to be implemented. To effectively design these requirements, insights into socio-technical systems can be gained through agent-based modelling and simulation. To implement such social concepts in agent-based models of infrastructure systems, we designed a modelling framework called MAIA, based on the Institutional Analysis and Development framework of Elinor Ostrom. This paper will explain how MAIA can be used to model a biogas energy infrastructure in the Netherlands. Citation: Verhoog, R., Ghorbani, A., Dijkema, G.P.J. & Weijnen, M.P.C. (2014). Structuring Socio-Technical Complexity in Infrastructure Systems: The Biogas System. In: Campbell P. and Perez P. (Eds), Proceedings of the International Symposium of Next Generation Infrastructure, 1-4 October 2013, SMART Infrastructure Facility, University of Wollongong, Australia

Modelling socio-ecological systems with MAIA: A biogas infrastructure simulation

Similar to other renewable energy technologies, the development of a biogas infrastructure in the Netherlands is going through social, institutional and ecological evolution. To study this complex evolutionary process, we built a comprehensive agent-based model of this infrastructure. We used an agent-based modelling framework called MAIA to build this model with the initial motivation that it facilitates modelling complex institutional structures. The modelling experience however proved that MAIA can also act as an integrated solution to address other major modelling challenges identified in the literature for modelling evolving socio-ecological systems. Building on comprehensive reviews, we reflect on our modelling experience and address four key challenges of modelling evolving socio-ecological systems using agents: (1) design and parameterization of models of agent behaviour and decision-making, (2) system representation in the social and spatial dimension, (3) integration of sociodemographic, ecological, and biophysical models, (4) verification, validation and sensitivity analysis of such ABMs

Value dynamics in energy democracy: An exploration of community energy initiatives

In the European Union, energy democracy (ED) is considered a socially desirable policy goal. One way to achieve ED is through empowering local communities to become agents of value change who can pursue more sustainable and equitable energy provision with community energy initiatives (CEI). However, such people-driven value change is complex in nature. CEIs are multifaceted sociotechnical systems that bring together sets of values and are composed of agents (i.e., people), technologies (e.g., solar panels), and institutions (e.g., renewable energy policies). Yet not much research is conducted into how values relate and overlap within this complex nexus of people - technology - institutions on a pathway to democratizing the energy sector through civic participation. In this paper, we spotlight value relationality to capture the diversity in the value landscape of people-driven energy transitions. We claim that each sociotechnical system has “climate” of its own, or value dynamics, induced by interrelating values. We propose an account that captures value dynamics, explores value sets brought together by the different sociotechnical components of CEIs and investigates various ways in which these value sets interrelate. To elucidate value dynamics in the context of CEIs, we have conducted a literature review, a content analysis of regional, national (i.e., Dutch), and EU policies, and expert interviews in two illustrative case studies. We finalize the paper with recommendations for further research on value dynamics in CEIs across various sociotechnical contexts

Shared Strategies in Artificial Agent Societies

A shared strategy is a social concept that refers to a type of behavioural pattern that is followed by a significant number of individuals although it is, prima facie, not associated with an obligation or a prohibition. E. Ostrom has argued in favour of the pertinence of social strategies for institutional design and evolution and proposed a characterization suggestive of formal treatment. However, shared strategies as such have not been explicitly used in the context of regulated MAS in spite of their relevance and their affinity to more standard normative notions, of which a rich tradition exists in MAS research. In this paper, we discuss the notion of shared strategy, characterize its distinguishing features, propose its formalization using a temporal epistemic logic, and explore its potential use in regulated multi-agent systems. © Springer-Verlag 2013.This research was partly funded by the COST Action IC0801 “Agreement Technologies” GrantPeer Reviewe