Policy change and learning: Implementing EU environmental policies affecting agriculture

This thesis aims to show whether and how the implementation of the EU environmental policy could be improved through policy learning. The results are based on two case studies: the development of agri-environmental policy in Finland and the implementation of the Water Framework Directive(WFD)in Ireland. The institutional analysis shows that the institutional structures changed due to the membership: the formal structures changed almost overnight and, as a result of increased cross-sectoral cooperation and policy learning, the informal structures also changed. The implementation of agri-environmental policy was studied in one administrative region, namely Uusimaa, located in southern Finland. The adaptation of EU environmental policies is an interesting research topic, not only because of the policy process itself but also because of the actors and context involved

Overlapping Coalitions, Bargaining and Networks

This paper extends the theory of endogenous coalition formation, with complete information and transferable utility, to the overlapping case. We propose a cover function bargaining game which allows the formation of overlapping coalitions at equilibrium. We show the existence of subgame perfect equilibrium and provide an algorithm to compute this equilibrium in the symmetric case. As an application, we establish an interesting link with the formation of networks.Overlapping Coalitions, Cover Function, Bargaining, Symmetric Game, Network

Coalition Formation Games for Distributed Cooperation Among Roadside Units in Vehicular Networks

Vehicle-to-roadside (V2R) communications enable vehicular networks to support a wide range of applications for enhancing the efficiency of road transportation. While existing work focused on non-cooperative techniques for V2R communications between vehicles and roadside units (RSUs), this paper investigates novel cooperative strategies among the RSUs in a vehicular network. We propose a scheme whereby, through cooperation, the RSUs in a vehicular network can coordinate the classes of data being transmitted through V2R communications links to the vehicles. This scheme improves the diversity of the information circulating in the network while exploiting the underlying content-sharing vehicle-to-vehicle communication network. We model the problem as a coalition formation game with transferable utility and we propose an algorithm for forming coalitions among the RSUs. For coalition formation, each RSU can take an individual decision to join or leave a coalition, depending on its utility which accounts for the generated revenues and the costs for coalition coordination. We show that the RSUs can self-organize into a Nash-stable partition and adapt this partition to environmental changes. Simulation results show that, depending on different scenarios, coalition formation presents a performance improvement, in terms of the average payoff per RSU, ranging between 20.5% and 33.2%, relative to the non-cooperative case.Comment: accepted and to appear in IEEE Journal on Selected Areas in Communications (JSAC), Special issue on Vehicular Communications and Network

Instant Efficient Pollution Abatement under Non-Linear Taxation and Asymmetric Information: The Differential Tax Revisited

This paper analyzes incentives for polluting firms to exchange abatement cost information under the non-linear pollution tax scheme (‘differential tax’) introduced by Kim and Chang [J. Regul. Econom. 5, 1993, 193-197]. It shows that polluting firms have - under mild conditions - an incentive to join a coalition whose members mutually truthfully exchange information as well as commit themselves with respect to their abatement decisions. As a result, the differential tax triggers instantly - i.e. no abatement adaptation is needed – efficient abatement levels without the regulator knowing marginal abatement costs. Consequently, this paper shows that differential taxation results in lower social costs than traditional non-linear taxation which triggers efficient emissions only after a period of non-efficient abatement.Externalities, Pollution taxes, Coalition formation, Non-linear taxation, Asymmetric information, Co-operative game theory

Coalition Formation Games for Collaborative Spectrum Sensing

Collaborative Spectrum Sensing (CSS) between secondary users (SUs) in cognitive networks exhibits an inherent tradeoff between minimizing the probability of missing the detection of the primary user (PU) and maintaining a reasonable false alarm probability (e.g., for maintaining a good spectrum utilization). In this paper, we study the impact of this tradeoff on the network structure and the cooperative incentives of the SUs that seek to cooperate for improving their detection performance. We model the CSS problem as a non-transferable coalitional game, and we propose distributed algorithms for coalition formation. First, we construct a distributed coalition formation (CF) algorithm that allows the SUs to self-organize into disjoint coalitions while accounting for the CSS tradeoff. Then, the CF algorithm is complemented with a coalitional voting game for enabling distributed coalition formation with detection probability guarantees (CF-PD) when required by the PU. The CF-PD algorithm allows the SUs to form minimal winning coalitions (MWCs), i.e., coalitions that achieve the target detection probability with minimal costs. For both algorithms, we study and prove various properties pertaining to network structure, adaptation to mobility and stability. Simulation results show that CF reduces the average probability of miss per SU up to 88.45% relative to the non-cooperative case, while maintaining a desired false alarm. For CF-PD, the results show that up to 87.25% of the SUs achieve the required detection probability through MWCComment: IEEE Transactions on Vehicular Technology, to appea

Coalitional Games for Distributed Collaborative Spectrum Sensing in Cognitive Radio Networks

Collaborative spectrum sensing among secondary users (SUs) in cognitive networks is shown to yield a significant performance improvement. However, there exists an inherent trade off between the gains in terms of probability of detection of the primary user (PU) and the costs in terms of false alarm probability. In this paper, we study the impact of this trade off on the topology and the dynamics of a network of SUs seeking to reduce the interference on the PU through collaborative sensing. Moreover, while existing literature mainly focused on centralized solutions for collaborative sensing, we propose distributed collaboration strategies through game theory. We model the problem as a non-transferable coalitional game, and propose a distributed algorithm for coalition formation through simple merge and split rules. Through the proposed algorithm, SUs can autonomously collaborate and self-organize into disjoint independent coalitions, while maximizing their detection probability taking into account the cooperation costs (in terms of false alarm). We study the stability of the resulting network structure, and show that a maximum number of SUs per formed coalition exists for the proposed utility model. Simulation results show that the proposed algorithm allows a reduction of up to 86.6% of the average missing probability per SU (probability of missing the detection of the PU) relative to the non-cooperative case, while maintaining a certain false alarm level. In addition, through simulations, we compare the performance of the proposed distributed solution with respect to an optimal centralized solution that minimizes the average missing probability per SU. Finally, the results also show how the proposed algorithm autonomously adapts the network topology to environmental changes such as mobility.Comment: in proceedings of IEEE INFOCOM 200

Status-Seeking in Hedonic Games with Heterogeneous Players

We study hedonic games with heterogeneous player types that reflect her nationality, ethnic background, or skill type. Agents' preferences are dictated by status-seeking where status can be either local or global. The two dimensions of status define the two components of a generalized constant elasticity of substitution utility function. In this setting, we characterize the core as a function of the utility's parameter values and show that in all cases the corresponding cores are non-empty. We further discuss the core stable outcomes in terms of their segregating versus integrating properties.Coalitions, Core, Stability, Status-seeking

Hedonic Coalition Formation for Distributed Task Allocation among Wireless Agents

Autonomous wireless agents such as unmanned aerial vehicles or mobile base stations present a great potential for deployment in next-generation wireless networks. While current literature has been mainly focused on the use of agents within robotics or software applications, we propose a novel usage model for self-organizing agents suited to wireless networks. In the proposed model, a number of agents are required to collect data from several arbitrarily located tasks. Each task represents a queue of packets that require collection and subsequent wireless transmission by the agents to a central receiver. The problem is modeled as a hedonic coalition formation game between the agents and the tasks that interact in order to form disjoint coalitions. Each formed coalition is modeled as a polling system consisting of a number of agents which move between the different tasks present in the coalition, collect and transmit the packets. Within each coalition, some agents can also take the role of a relay for improving the packet success rate of the transmission. The proposed algorithm allows the tasks and the agents to take distributed decisions to join or leave a coalition, based on the achieved benefit in terms of effective throughput, and the cost in terms of delay. As a result of these decisions, the agents and tasks structure themselves into independent disjoint coalitions which constitute a Nash-stable network partition. Moreover, the proposed algorithm allows the agents and tasks to adapt the topology to environmental changes such as the arrival/removal of tasks or the mobility of the tasks. Simulation results show how the proposed algorithm improves the performance, in terms of average player (agent or task) payoff, of at least 30.26% (for a network of 5 agents with up to 25 tasks) relatively to a scheme that allocates nearby tasks equally among agents.Comment: to appear, IEEE Transactions on Mobile Computin

Polarization of coalitions in an agent-based model of political discourse

Political discourse is the verbal interaction between political actors in a policy domain. This article explains the formation of polarized advocacy or discourse coalitions in this complex phenomenon by presenting a dynamic, stochastic, and discrete agent-based model based on graph theory and local optimization. In a series of thought experiments, actors compute their utility of contributing a specific statement to the discourse by following ideological criteria, preferential attachment, agenda-setting strategies, governmental coherence, or other mechanisms. The evolving macro-level discourse is represented as a dynamic network and evaluated against arguments from the literature on the policy process. A simple combination of four theoretical mechanisms is already able to produce artificial policy debates with theoretically plausible properties. Any sufficiently realistic configuration must entail innovative and path-dependent elements as well as a blend of exogenous preferences and endogenous opinion formation mechanisms

Economic Evaluation of Climate Change Impacts and Adaptation in Italy

The paper deals with the social and economic dimensions of climate change impacts and adaptation in Italy. The ultimate aim of the paper is to provide policy makers and experts with a conceptual framework, as well as methodological and operational tools for dealing with climate change impacts and adaptation from an economic perspective. In order to do so, first a conceptual and theoretical framework of the economic assessment of climate change impacts is presented and the state of the art about impact assessment studies is briefly analysed. Then, the Italian case is taken into account, by underlying the main impacts and adaptation challenges that are likely to be implied by climate change in the next decades. The analysis of the Italian case is particularly addressed through the description of the methodology and results of two case studies. The first one, dealing mainly with impact assessment, is carried out at the national level and is part of a EC funded project on Weather Impacts on Natural, Social and Economic Systems (WISE). The second one is carried out at the local level and focuses on sea level rise impacts and adaptation in a plane south of Rome. The two case studies allow to propose simple and flexible methodologies for the economic impact assessment and the economic valuation of adaptation strategies.Climate change, Economic impact assessment, Adaptation, Cost benefit analysis