Agent-based model

Summary

An agent-based model (ABM) is a computational model for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) in order to understand the behavior of a system and what governs its outcomes. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo methods are used to understand the stochasticity of these models. Particularly within ecology, ABMs are also called individual-based models (IBMs). A review of recent literature on individual-based models, agent-based models, and multiagent systems shows that ABMs are used in many scientific domains including biology, ecology and social science. Agent-based modeling is related to, but distinct from, the concept of multi-agent systems or multi-agent simulation in that the goal of ABM is to search for explanatory insight into the collective behavior of agents obeying simp

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Research problem: Housing is responsible for a considerable part of global resource consumption. In Switzerland, it accounts for almost one third of the country's CO2 emissions and half of the total energy demand. Thus, housing plays an important role in the transition to sustainable development. Housing has been thoroughly studied from a disciplinary perspective, e.g., economics, social sciences, psychology, engineering. However, little attention has been paid to housing as a system of interrelated actors, e.g., developers, owners, tenants and state, whose actions might be described by different disciplines. Aim: The aim of this thesis is to investigate how a change in the construction practices of property owners in combination to a more space-efficient allocation of dwellings to households and a behavioural change of tenants can achieve a substantial reduction in the environmental impact of housing. This dissertation focuses on the interrelations of housing actors, concentrating mainly on the property owners and explores which measures and to what extent can lead to a reduction of space consumption of housing.Methods: Housing is characterised by a high level of complexity, therefore a transdisciplinary approach is adopted. Firstly, the Swiss housing market and its unique attributes are studied. However, in this thesis, we study a subset of the Swiss rental housing market; it comprises two housing cooperatives: ABZ in Zurich and SCHL in Lausanne as well as the insurer and asset manager Swiss Mobiliar. Their housing stocks, of approximately 10,000 dwellings, are examined in depth and are used as a case study. Extensive data gathering allowed to create an exhaustive inventory of the building stock of the three property owners. The data on tenants was limited, thus, we conducted a tenant survey. Furthermore, a series of workshops with both tenants and property owners were organised to study their decision-making processes. A bottom-up agent-based model (ABM) is built, which portrays the case study housing system. The main actors of the rental housing market (property owners and households) are represented in the model by agents; the owner agents make decisions about their building stock and tenants, while the household agents choose a dwelling based on their needs and housing preferences. The dynamic evolution of both owners and households and the interaction between them is simulated in the model and allows the study of emergent phenomena. The present thesis attempts the assessment of the environmental impact of housing through the lens of housing sufficiency. Space consumption, in terms of dwelling surface and floor area per capita, is considered as the largest determinant of resource consumption.Results: The simulation results show that measures taken to decrease the environmental impact of housing and space consumption are inadequate if owners do not change their construction practices and households do not actively change their housing behaviour. Most measures explored in this thesis, if implemented individually, succeed in reducing the rate of increase in space consumption but fail to reverse the upward trend. A more space-efficient allocation of dwellings to households proves to have a certain effect. However, only when combined with other measures, such as the densification of the existing building stock and a change in construction practices, a significant decrease of environmental impact is observed.

EPFL2022

Policymaking is a complex process that has been studied using policy process theories almost exclusively. These theories have been built using a large number of qualitative cases. Such methods are useful for theory building but remain limited for theory exploration and policy advice. On a different front, socio-technical system (STS) simulations are often used to test the impact and effectiveness of policies. This is done by using policy scenarios. This manner of dealing with deep uncertainty disregards the dynamic aspect of the policy process and of the way STS interact with policies. The objective of this dissertation is to present an approach that can be used to systematically model and simulate the policy process. This dissertation demonstrates how such a model can be used in these two widely different applications to explore the policy process theories and to better account for deep uncertainty in STS simulations. In the first part of the dissertation, I present a common language. It considers four building blocks using concepts from prominent theories as requirements to any model of the policy process: time, the policy arena, actors and the environment, and the actor interactions. Additionally, in this part, I argue why agent-based modelling is best suited to simulate the policy process. Finally, I present the hybrid modelling approach that is used to incorporate the policy process model into already existing STS models. The second part focuses on the simplest implementation model. This model is the first use of the common language and is entitled simplest implementation as the common language is used to build the simplest model possible capable of emulating the policy process. It is created to demonstrate the potential of the common language and is tested with three different STS. A predation model is used to present the possibilities stemming from this simplest implementation model. It is then added to a model of the Swiss electricity market to demonstrate what benefits the endogenisation of the policy process can have on the study of a complex STS. As a third example, the policy process model is added to a system dynamics model of flood safety in The Netherlands to demonstrate its versatility. The third part of this dissertation consists of the advocacy coalition framework (ACF) implementation model. In this part, I present a model, also developed using the common language, that is aimed at emulating the ACF as closely as possible. The ACF being a complex framework, this implementation is done in steps of increasing complexity. The first step introduces policy learning to the model, the second introduces coalitions, the third and fourth steps introduce aspects of partial knowledge and imperfect information. This ACF implementation model is also demonstrated using first a predation model and second a model of the Swiss electricity market. In conclusion, this dissertation shows that it is possible to model the policy process. However it was shown that the policy process theories could benefit from additional and more focused studies so that behaviours and mechanisms can be better understood. This work can be the first step to such studies. It was also shown that introducing the policy process in a STS simulation can be useful to better understand said system. This approach allows for an easy integration to already existing models. Finally, this work can be extended by looking at other theories or different applications.

EPFL2021

Crossing properties of soil saturation, defined as the duration and excursion of soil saturation below and above certain thresholds, are key variables to ecosystem functioning and evolution by primarily influencing the plant and soil microbes physiological dynamics. Under climate change, the variability in the precipitation patterns is expected to be more ubiquitous and directly translate to a shift in soil saturation levels. This, in turn, will influence crossing properties of soil saturation and thus be expected to leave a mark on ecosystems. However, the lack of a deep understanding of the links between biological processes and the change in soil saturation patterns hinders foretelling the impact of climate variability on ecohydrological systems even at the smallest scale, that is, the level of a single plant.To that end, this thesis presents experimental results from laboratory soil column experiments and extensive computational studies on the interactions between soil saturation and biological activities, that is, plants and microbes. To this aim, the depth-time soil saturation patterns are mapped by means of modeling the transport processes of relevance and experimental tools at a minimal hydrological control volume in search for upscaling methods. In this context, two modeling approaches can be employed. Physically based models that explicitly represent transport processes with high costs of application at larger scales. Age-based models that rely on generic functions with a focus on time past since arrival, that is, the age of event water in the storage. This thesis work combines models (HYDRUS-1D as physically based and tran-SAS as age-based) with soil column experimental data and Bayesian inference methods to explore the links between age characteristics and transport processes. In this thesis, data from four different experimental designs on monthly to yearly timescale under varied environmental conditions are examined in terms of tracer type, precipitation pattern, vegetation, soil type, resolution and type of collected data. Of the modeled data, two sets of results from specific experiments were carried out within the framework of this thesis.This thesis addresses also the role of the balance between dispersive and convective forces, known as Péclet number, in controlling the shape of age functions in drainage. While sole reliance on drainage flow and tracer data (reflective of Péclet number) suffice to capture age dynamics in drainage, un- certainties may arise for predictions on (evapo)transpiration. This thesis deals also with the role of root distributions as controls in determining the age to root uptake and shows plants with similar uniform-equivalent root distribution render very similar age dynamics. It was shown in this thesis that nitrate consumption by microbes can be linked to age characteristics of a conservative tracer and that the relation between microbial respiration and soil saturation may bear more complexity than is currently integrated in most models. Overall, this thesis lays steps to the development of modeling tools with high predictive power for soil saturation by originating upscaling methods and bridging the gaps between physically based and age-based models with a view on the consequences of (possi- bly changing) variable soil saturation on adaptations of microbial communities and their metabolic product.

EPFL2022

EPFL2021