Research Items (17)
Social–ecological systems (SES) research underlines the tremendous impact of human behaviour on planet Earth. To enable a sustainable course of humanity, the integration of human cognition in SES research is crucial for better understanding the processes leading to and involved in human behaviour. However, this integration is proving a challenge, not only in terms of diverging ontological and epistemological perspectives, but also—and this has received little attention in SES research—in terms of (lacking) precision of communication regarding cognition. SES scholars often implicitly disagree on the meaning of this broad concept due to unexpressed underlying assumptions and perspectives. This paper raises awareness for the need to communicate clearly and mindfully about human cognition by exemplifying common communication pitfalls and ways of preventing them. We focus on the concept of cognition itself and provide aspects of cognition that need to be communicated explicitly, i.e. different objects of investigation and levels of description. Lastly, we illustrate means of overcoming communication pitfalls by the example of rationality.
- Mar 2017
- Advances in Social Simulation 2015
Occupy, the Gezi park movement, the Maidan protests, or the recent solidarity marches for Charlie Hebdo—since the uprisings of the Arab Spring, we could observe many examples of on-site protests on big squares and streets being accompanied by waves of collective action in social media. We present the design stage of an agent-based model that will allow us to explore the following questions: What role does social media play in street protests? How does social media usage influence the dynamics of collective action during street protests? Do social media affect the speed, scale, fluctuation, duration of the protest at large, and in which way? Do they impact specific crowd patterns, e.g., the development of groups within groups? The model builds on and integrates existing models of social media, protests, and crowd behavior to simulate the dynamics of street protests in an urban setting. Our central aim is to compare scenarios with intense, moderate, and no social media usage by the protesters.
- Jan 2017
Formal models are commonly used in natural resource management (NRM) to study human-environment interactions and inform policy making. In the majority of applications, human behaviour is represented by the rational actor model despite growing empirical evidence of its shortcomings in NRM contexts. While the importance of accounting for the complexity of human behaviour is increasingly recognized, its integration into formal models remains a major challenge. The challenges are multiple: i) there exist many theories scattered across the social sciences, ii) most theories cover only a certain aspect of decision-making, iii) they vary in their degree of formal-ization, iv) causal mechanisms are often not specified. We provide a framework-MoHuB (Modelling Human Behavior)-to facilitate a broader inclusion of theories on human decision-making in formal NRM models. It serves as a tool and common language to describe, compare and communicate alternative theories. In doing so, we not only enhance understanding of commonalities and differences between theories, but take a first step towards tackling the challenges mentioned above. This approach may enable modellers to find and formalize relevant theories , and be more explicit and inclusive about theories of human decision making in the analysis of social-ecological systems.
Cooperation amongst resource users holds the key to overcoming the social dilemma that characterizes community-based common-pool resource management. But is cooperation alone enough to achieve sustainable resource use? The short answer is no. Developing management strategies in a complex social-ecological environment also requires ecological knowledge and approaches to deal with perceived environmental uncertainty. Recent behavioral experimental research indicates variation in the degree to which a group of users can identify a sustainable exploitation level. In this paper, we identify social-ecological micro-foundations that facilitate cooperative sustainable common-pool resource use. We do so by using an agent-based model (ABM) that is informed by behavioral common-pool resource experiments. In these experiments, groups that cooperate do not necessarily manage the resource sustainably, but also over- or underexploit. By reproducing the patterns of the behavioral experiments in a qualitative way, the ABM represents a social-ecological explanation for the experimental observations. We find that the ecological knowledge of each group member cannot sufficiently explain the relationship between cooperation and sustainable resource use. Instead, the development of a sustainable exploitation level depends on the distribution of ecological knowledge among the group members, their influence on each other’s knowledge, and the environmental uncertainty the individuals perceive. The study provides insights about critical social-ecological micro-foundations underpinning collective action and sustainable resource management. These insights may inform policy-making, but also point to future research needs regarding the mechanisms of social learning, the development of shared management strategies and the interplay of social and ecological uncertainty.
Of the many crowd behavior models, very few have been used in assisting crowd management practice. This lack of usage is partly due to crowd management involving a diversity of situations that require competencies in observing, sense-making, anticipating and acting. Crowd research is similarly scattered across disciplines and needs integration to advance the field towards supporting practice. To address these needs, we present inCrowd, an integrated framework detailing a high-level architecture of a decision-support system for crowd management and model development. It also offers a lens for categorizing crowd literature, allowing us to present a structured literature review.
We argue that the capacity to live life to the benefit of self and others originates in the defining properties of life. These lead to two modes of cognition; the coping mode that is preoccupied with the satisfaction of pressing needs and the co-creation mode that aims at the realization of a world where pressing needs occur less frequently. We have used the Rule of Conservative Changes – stating that new functions can only scaffold on evolutionary older, yet highly stable functions – to predict that the interplay of these two modes define a number of core functions in psychology associated with moral behavior. We explore this prediction with five examples reflecting different theoretical approaches to human cognition and action selection. We conclude the paper with the observation that science is currently dominated by the coping mode and that the benefits of the co-creation mode may be necessary to generate realistic prospects for a modern synthesis in the sciences of the mind.
- Jan 2014
- Advances in Social Simulation
This paper describes the design phase of an ABM case study of Bali irrigation. The aim of the model is to explain the differences in the ability of rice paddy farmers to collectively adapt through cooperation. The model should allow exploring factors affecting self organisation within and between rice paddy farmer communities. The exercise of the ABM case study aims to move abstract models (theory) closer to real world phenomena, which requires contextualisation. This paper focuses on the first steps in model contextualisation: model selection and specification for the Bali irrigation case.
The use of computer simulations in crowd research is a powerful tool to describe and analyse complex social systems. This paper presents CROSS, a generic framework to model crowd simulations as a social scientific tool for understanding crowd behaviour. In CROSS, individuals are represented by social-cognitive agents that are affected by their social and physical surroundings and produce cognition-based behaviour and behaviour patterns. Understanding is sought by relating intra- and inter-individual levels of behaviour generation with behaviour pattern emergence at group level. By specifying the CROSS framework for a festival context we demonstrate how CROSS meets the need for a theory that reflects the dynamic interplay between individuals and their environment as well as the need for a method that allows for testing.
- Aug 2013
To implement or continue water management strategies social support is needed. Social support highly depends on people's perspectives on water. However, these perspectives are not static and may change over time leading to changes in social support for strategies. Therefore, sustainable water management strategies should be robust. Robust strategies are able to cope with changing social and environmental developments. Lacking robustness runs the risk of losing social support, which may force policymakers into sudden or expensive measures. We use the Perspectives Method to analyze the present Dutch policy perspective and the dominant perspective on water among Dutch water professionals, by respectively studying the Dutch Delta report and questionnaire outputs and distinguishing between Hierarchical, Egalitarian, Individualistic and Fatalistic perspectives. A comparison between the policy and professional perspective shows similarities and differences. Topics regarding drought, water supply, and waters' relation to spatial planning need serious reconsideration to guarantee enough present and future social support to implement the measures suggested in the policy report.
- Jan 2013
When talking to fellow modellers about the feedback we get on our simulation models the conversation quickly shifts to anecdotes of rejective scepticism. Many of us experience that they get only few remarks, and especially only little helpful constructive feedback on their simulation models. In this forum paper, we give an overview and reflections on the most common criticisms experienced by ABM modellers. Our goal is to start a discussion on how to respond to criticism, and particularly rejective scepticism, in a way that makes it help to improve our models and consequently also increase acceptance and impact of our work. We proceed by identifying common criticism on agent-based modelling and social simulation methods and show where it shifts to rejection. In the second part, we reflect on the reasons for rejecting the agent-based approach, which we mainly locate in a lack of understanding on the one hand, and academic territorialism on the other hand. Finally, we also give our personal advice to socsim modellers of how to deal with both forms of rejective criticism. http://jasss.soc.surrey.ac.uk/16/4/13.html
Social conflict entails a variety of social phenomena, including international conflict, civil war, genocide, organized violence, insurgencies and rebellions, terrorism, riots, etc. Given the heterogeneity of social phenomena encompassed by this notion, it is not surprising that a variety of methodological and theoretical approaches have been applied to study it, ranging from formal game theoretic models to the hermeneutics of narratives. Social conflict has also been studied by means of complex systems research methods, such as agent-based social simulation. We conduct a review of the main formal-theoretical approaches to social conflict including agent-based modeling. We promote the usage of agent-based social simulation for it affords shedding light onto the nature of generative processes related to social conflict. We discuss the implications of such an approach to the study of social conflict against orthodox research designs and point toward its advantages which may facilitate development of more adequate conflict prevention and conflict management procedures.
We discuss the field of formal, in particular computational methods to study social conflict, in order to approximate the Weberian notion of verstehen. While traditional theoretical distinctions, such as structuralist and interactionalist approaches, can be revealed in clas-sical formal methods, agent-based modeling can be couched in such terms as complexity, analytical sociology, and critical realism. The self-understanding of these research traditions – methodologically as well as theoretically – might be able to induce impulses to orthodox conflict re-search's research designs and might also shed light onto the nature of the generative processes related to social conflict. So far such promises remain under-explored.
Crowds and riots in contemporary conflict are only little un-derstood. However, it is fairly well understood that the emergence of crowds and riots in conflict regions has a severe and lasting impact on the security situation. On the basis of an existing and cross-validated model of Afghan power structures we demonstrate what role opinion dynamics play in the evolution of a critical social condition preceding the emer-gence of crowds and riots. It is explained how information on security incidences spreads within an artificial society and when such a turning point is reached. The influence of network structures on the spread of information and the role opinion leaders play is explored. We find that small world network structures lead to dynamics that are volatile, unpre-dictable and performative in nature. It is also shown that opinion leaders have a catalytic effect on the information distribution processes. These findings bear importance for policy makers and practitioners in the field.
We present a new civilian crowd simulator for the Robocup Rescue Simulation that allows to represent large numbers of civilians and in which psy-chologically and socially plausible crowd behavior emerges. As a new challenge for the Rescue Simulation competition, the simulator also allows police agents to indirectly influence crowd behavior by temporarily blocking roads. The simulator can be used as an stand-alone tool for interactive or automatic testing of strate-gies for crowd control, but will also be integrated into the Rescue Simulation environment.
This paper describes our approach in modelling goal-driven and situated behaviour. Numerous social phenomena are characterised by a diversity of behaviours shown, for instance crowd behaviour in an festival, demonstation, or riot context. To be able to reproduce and anal-yse such phenomena, we state the necessity of incorporating multiple goals and situatedness in terms of limited and subjective perception in modelling. Our approach in formalising this view is described and an example is given in terms a simple simulation of human behaviour at a festival terrain.