Modeling human decisions in coupled human and natural systems: Review of agent-based models

An, Li

doi:10.1016/j.ecolmodel.2011.07.010

Cited by 631 publications

(345 citation statements)

References 148 publications

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“…In social structuration theory [28], structure "is always both enabling and constraining, in virtue of the inherent relation between structure and agency". That is, social structure is a duality; in that it both drives the emergence of social structure and is a product of it [3].…”

Section: Emergence and Self-organizationmentioning

confidence: 99%

“…In this paper, we argue that the current theoretical approaches that seek to deal with the complexity of actualizing transitions to sustainability, do not fully appreciate the implications of complexity theory and hence remain restricted to modeling the mechanisms that drive the dynamic behaviors of complex systems (e.g., non-linear feedbacks, and leads and lags that are mediated by flows between stocks: see [3][4][5]). These are good at determining problems from a systems perspective, but not necessarily good for thinking about solutions.…”

Section: Modeling Complexity and Transitions To Sustainabilitymentioning

confidence: 99%

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Linking Complexity and Sustainability Theories: Implications for Modeling Sustainability Transitions

Peter

Swilling

2014

Sustainability

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Abstract:In this paper, we deploy a complexity theory as the foundation for integration of different theoretical approaches to sustainability and develop a rationale for a complexity-based framework for modeling transitions to sustainability. We propose a framework based on a comparison of complex systems' properties that characterize the different theories that deal with transitions to sustainability. We argue that adopting a complexity theory based approach for modeling transitions requires going beyond deterministic frameworks; by adopting a probabilistic, integrative, inclusive and adaptive approach that can support transitions. We also illustrate how this complexity-based modeling framework can be implemented; i.e., how it can be used to select modeling techniques that address particular properties of complex systems that we need to understand in order to model transitions to sustainability. In doing so, we establish a complexity-based approach towards modeling sustainability transitions that caters for the broad range of complex systems' properties that are required to model transitions to sustainability.

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Section: Emergence and Self-organizationmentioning

confidence: 99%

Section: Modeling Complexity and Transitions To Sustainabilitymentioning

confidence: 99%

Linking Complexity and Sustainability Theories: Implications for Modeling Sustainability Transitions

Peter

Swilling

2014

Sustainability

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“…Useful discussions of this issue can be found in [An, 2012;Grimm et al, 2010;Müller et al, 2014;Tesfatsion, 2016p]. See, also, Wallace et al [2015] for an exceptionally thoughtful attempt to develop presentation and evaluation protocols for agent-based models designed for policy purposes.…”

Section: Formentioning

confidence: 99%

Elements of Dynamic Economic Modeling: Presentation and Analysis

Tesfatsion

2017

Eastern Econ J

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The primary goal of these introductory notes is to promote the clear presentation and rigorous analysis of dynamic economic models, whether expressed in equation or agent-based form. A secondary goal is to promote the use of state-space modeling with its respect for historical process, for cause leading to effect without top-down imposition of global constraints. If economic modelers truly wish to respect the rationality of decision-makers, they should have the courage of their convictions; they should not be doing for their modeled decision-makers what in reality these decision-makers must do for themselves. These notes on dynamic economic modeling are designed for self-study by graduate students of economics. The focus is on general presentation and analysis principles for dynamic economic models expressible by means of state space models in initial value form.The state of a modeled system at any given time is a characterization of system aspects deemed by the modeler to be relevant for a speci ed purpose. Typically the only aspects 1 explicitly included in the state are aspects that can change over time; xed aspects are suppressed for ease of notation. For an economic system, the state typically includes the asset holdings, information, and beliefs of economic entities such as rms, consumers, and government policy makers.Hereafter, state space model will refer exclusively to a state space model in initial value form, that is, to a model that speci es how the state of a system changes over time, starting from a given state at an initial time t 0 [Aström and Murray, 2008, Ch. 2]. Roughly described, given any time t ≥ t 0 and time increment ∆t > 0, the state realized at time t + ∆t is postulated to be a function of the state realized at time t together with all inputs to the system between t and t + ∆t, where the inputs can include controls and random event realizations.These functional relationships are conditioned on exogenously speci ed functional forms and parameter values.

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“…Involving local communities in disaster risk reduction techniques can surely enhance their collective capacity to cope with climatic extremes (Wilhite 2002). Participatory modelling using fuzzy cognitive maps are increasingly being used in planning and decision-making (Vliet et al 2009;Lopolito et al 2011;An 2012;Jetter and Kok 2014). Understanding people's perception about the impact of drought on their livelihood assets gives a clear vision of the most impacted sectors and aids planning adaptation with regard to developing drought resilient livelihoods.…”

Section: Need Of Participatory Modelling-based Drought Studymentioning

confidence: 99%

Pathways for drought resilient livelihoods based on people’s perception

Singh

Chudasama

2016

Climatic Change

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Drought is among the most dreaded threats as far as natural disasters are concerned wielding, as it does, a significant impact on ecosystems, people's livelihoods, and the socioeconomic development of a country. A significantly large geographic area of India happens to be drought prone. In order to understand people's response to the impacts of drought and their coping strategies, it is crucial to understand their perceptions. Studies investigating community perceptions relevant to drought impacts and concomitant adaptive behaviours are rare in India. This paper documents communities' perceptions of impacts of drought on their livelihood assets and adaptation practices. It does this with the help of the fuzzy cognitive mapping approach in the Mahabubnagar district of India's Telangana state. In order to develop pathways for drought resilient livelihoods we ran simulations for future drought scenarios with various bundles of adaptation strategies enabling us to evaluate their effectiveness in providing resilience against drought. The study also tested the suitability of various activation rules and transformation functions, used for running simulations. Incorporating stakeholders' perceptions, knowledge and beliefs about impacts of droughts, and engaging them in the process of developing drought resilient livelihoods is expected to fine-tune the drought related policy-making.

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Modeling human decisions in coupled human and natural systems: Review of agent-based models

Cited by 631 publications

References 148 publications

Linking Complexity and Sustainability Theories: Implications for Modeling Sustainability Transitions

Linking Complexity and Sustainability Theories: Implications for Modeling Sustainability Transitions

Elements of Dynamic Economic Modeling: Presentation and Analysis

Pathways for drought resilient livelihoods based on people’s perception

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