865 research outputs found

    Leadership in social dilemmas

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    The objective of this thesis is to assess the prospects of leadership in the provision of public goods like climate change mitigation theoretically and empirically. The thesis is divided in four major sections. The theoretical Section I is based on classical narrow payoff maximizing economic agents and makes use of the Aggregative Game Approach (Cornes and Hartley 2007, Cornes 2016). Chapter 1 considers pioneering behaviour in coalition building and the resulting incentive effect on another group to form a coalition whereas Chapter 2 sheds light on the effects that technology transfers exert on the choice of a contribution technology by a group of countries. Chapter 3 addresses the question whether the sequential provision of a public good (in a Stackelberg game) increases public good supply as compared to simultaneous provision (in a Nash game) if one of two countries has the possibility to adopt an improved contribution technology. The theoretical analysis in Section I is complemented in Section II by an empirical example concerning leadership in technological progress of solar energy through its subsidization in Germany. The two remaining parts then move away from narrow payoff-maximizing agents. Both in public discussion and economic literature reciprocity is regarded as a key to successful cooperation and successful leadership. Consequently, Section III addresses the scope of reciprocity in economic experiments as well as in international relations (Chapter 5). Chapter 6 then investigates in an online experiment on MTurk the within-subject stability of reciprocal patterns across classification methods using a sequential public goods game (Fischbacher et al. 2001) on the one hand and a sequential prisoner’s dilemma (e.g. Miettinen et al. 2017) on the other hand. The final Section IV deals with the question whether it can be expected that leading-by-example is able to increase public good supply. A meta-analysis of the existing literature in Chapter 7 as well as a lab experiment that incorporates leadership in a dynamic public goods game with endowment carryover (Gächter et al. 2017) in Chapter 8 provide some answers to this question

    Towards representing human behavior and decision making in Earth system models. An overview of techniques and approaches

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    Today, humans have a critical impact on the Earth system and vice versa, which can generate complex feedback processes between social and ecological dynamics. Integrating human behavior into formal Earth system models (ESMs), however, requires crucial modeling assumptions about actors and their goals, behavioral options, and decision rules, as well as modeling decisions regarding human social interactions and the aggregation of individuals’ behavior. Here, we review existing modeling approaches and techniques from various disciplines and schools of thought dealing with human behavior at different levels of decision making. We demonstrate modelers’ often vast degrees of freedom but also seek to make modelers aware of the often crucial consequences of seemingly innocent modeling assumptions. After discussing which socioeconomic units are potentially important for ESMs, we compare models of individual decision making that correspond to alternative behavioral theories and that make diverse modeling assumptions about individuals’ preferences, beliefs, decision rules, and foresight. We review approaches to model social interaction, covering game theoretic frameworks, models of social influence, and network models. Finally, we discuss approaches to studying how the behavior of individuals, groups, and organizations can aggregate to complex collective phenomena, discussing agent-based, statistical, and representative-agent modeling and economic macro-dynamics. We illustrate the main ingredients of modeling techniques with examples from land-use dynamics as one of the main drivers of environmental change bridging local to global scales

    Price of unsustainability. Economic impacts of climate change

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    Global problems, rapid and massive regional changes in the 21st century call for genuine long-term, awareness, planning and well focused actions from both national governments and international organizations. This book wishes to contribute to building an innovative path of strategic views in handling the diverse challenges, and more emphatically, the economic impacts of climate change. Although the contributors of this volume represent several approaches, they all rely on some common grounds such as the costbenefit analysis of mitigation and adaptation, and on the need to present an in-depth theoretical and practical dimension. The research accounted for in this book tried to integrate and confront various types of economics approaches and methods, as well as knowledge from game theory to country surveys, from agricultural adaptation to weather bonds, from green tax to historical experience of human adaptation. The various themes and points of views do deserve the attention of the serious academic reader interested in the economics of climate change. We hope to enhance the spread of good solutions resulting from world wide disputes and tested strategic decisions. WAKE UP! It is not just the polar bears' habitat that is endangered, but the entire human form of life

    Location Awareness in Multi-Agent Control of Distributed Energy Resources

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    The integration of Distributed Energy Resource (DER) technologies such as heat pumps, electric vehicles and small-scale generation into the electricity grid at the household level is limited by technical constraints. This work argues that location is an important aspect for the control and integration of DER and that network topology can inferred without the use of a centralised network model. It addresses DER integration challenges by presenting a novel approach that uses a decentralised multi-agent system where equipment controllers learn and use their location within the low-voltage section of the power system. Models of electrical networks exhibiting technical constraints were developed. Through theoretical analysis and real network data collection, various sources of location data were identified and new geographical and electrical techniques were developed for deriving network topology using Global Positioning System (GPS) and 24-hour voltage logs. The multi-agent system paradigm and societal structures were examined as an approach to a multi-stakeholder domain and congregations were used as an aid to decentralisation in a non-hierarchical, non-market-based approach. Through formal description of the agent attitude INTEND2, the novel technique of Intention Transfer was applied to an agent congregation to provide an opt-in, collaborative system. Test facilities for multi-agent systems were developed and culminated in a new embedded controller test platform that integrated a real-time dynamic electrical network simulator to provide a full-feedback system integrated with control hardware. Finally, a multi-agent control system was developed and implemented that used location data in providing demand-side response to a voltage excursion, with the goals of improving power quality, reducing generator disconnections, and deferring network reinforcement. The resulting communicating and self-organising energy agent community, as demonstrated on a unique hardware-in-the-loop platform, provides an application model and test facility to inspire agent-based, location-aware smart grid applications across the power systems domain

    Investigation of Game-Theoretic Mechanisms for the Valuation of Energy Resources

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    Electricity systems are facing the pressure to change in response to the effects of new technology, particularly the proliferation of renewable technologies (such as solar PV systems and wind generation) leading to the retirement of traditional generation technologies that provide stabilising inertia. These changes create an imperative to consider potential future market structures to facilitate the participation of distributed energy resources (DERs; such as EVs and batteries) in grid operation. However, this gives rise to general questions surrounding the ethics of market structures and how they could be fairly applied in future electricity systems. Particularly the most basic question "how should electricity be valued and traded" is fundamentally a moral question without any easy answer. We give a survey of philosophical attitudes around such a question, before presenting a series of ways that these intuitions have been cast into mathematics, including: the Vickrey-Clarke-Groves mechanism, Locational Marginal Pricing, the Shapley Value, and Nash bargaining solution concepts. We compared these different methods, and attempted a new synthesis that brought together the best features of each of them; called the 'Generalised Neyman and Kohlberg Value' or the GNK-value for short. The GNK value was developed as a novel bargaining solution concept for many player non-cooperative transferable utility generalised games, and thus it was intrinsically flexible in its application to various aspects of powersystems. We demonstrated the features of the GNK-value against the other mathematical solutions in the context of trading the immediate consumption/generation of power on small sized networks under linear-DC approximation, before extending the computation to larger networks. The GNK value proved to be difficult to compute for large networks but was shown to be approximable for larger networks with a series of sampling techniques and a proxy method. The GNK value was ethically compared to other mechanisms with the unfortunate discovery that it allowed for participants to be left worse-off for participating, violating the ethical notion of 'euvoluntary exchange' and 'individual rationality'; but was offered as an interesting innovation in the space of transferable utility generalised games notwithstanding. For sampling the GNK value, there was a range of new and different techniques developed for stratified random sampling which iteratively minimise newly derived concentration inequalities on the error of the sampling. These techniques were developed to assist in the computation of the GNK value to larger networks, and they were evaluated in the context of sampling synthetic data, and in computation of the Shapley Value of cooperative game theory. These new sampling techniques were demonstrated to be comparable to the more orthodox Neyman sampling method despite not having access to stratum variances
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