Market microstructure studies the process of exchanging assets underexplicit trading rules. With algorithmic trading and high-frequencytrading, modern financial markets have seen profound changes in marketmicrostructure in the last 5 to 10 years. As a result, previously establishedmethods in the field of market microstructure becomes oftenfaulty or insufficient. Machine learning and, in particular, reinforcementlearning has become more ubiquitous in both finance and otherfields today with applications in trading and optimal execution. This thesisuses reinforcement learning to understand market microstructureby simulating a stock market based on NASDAQ Nordics and trainingmarket maker agents on this stock market. Simulations are run on both a dealer market and a limit orderbook marketdifferentiating it from previous studies. Using DQN and PPO algorithmson these simulated environments, where stochastic optimal controltheory has been mainly used before. The market maker agents successfullyreproduce stylized facts in historical trade data from each simulation,such as mean reverting prices and absence of linear autocorrelationsin price changes as well as beating random policies employed on thesemarkets with a positive profit & loss of maximum 200%. Other tradingdynamics in real-world markets have also been exhibited via theagents interactions, mainly: bid-ask spread clustering, optimal inventorymanagement, declining spreads and independence of inventory and spreads, indicating that using reinforcement learning with PPO and DQN arerelevant choices when modelling market microstructure. / Marknadens mikrostruktur studerar hur utbytet av finansiella tillgångar sker enligt explicita regler. Algoritmisk och högfrekvenshandel har förändrat moderna finansmarknaders strukturer under de senaste 5 till 10 åren. Detta har även påverkat pålitligheten hos tidigare använda metoder från exempelvis ekonometri för att studera marknadens mikrostruktur. Maskininlärning och Reinforcement Learning har blivit mer populära, med många olika användningsområden både inom finans och andra fält. Inom finansfältet har dessa typer av metoder använts främst inom handel och optimal exekvering av ordrar. I denna uppsats kombineras både Reinforcement Learning och marknadens mikrostruktur, för att simulera en aktiemarknad baserad på NASDAQ i Norden. Där tränas market maker - agenter via Reinforcement Learning med målet att förstå marknadens mikrostruktur som uppstår via agenternas interaktioner. I denna uppsats utvärderas och testas agenterna på en dealer – marknad tillsammans med en limit - orderbok. Vilket särskiljer denna studie tillsammans med de två algoritmerna DQN och PPO från tidigare studier. Främst har stokastisk optimering använts för liknande problem i tidigare studier. Agenterna lyckas framgångsrikt med att återskapa egenskaper hos finansiella tidsserier som återgång till medelvärdet och avsaknad av linjär autokorrelation. Agenterna lyckas också med att vinna över slumpmässiga strategier, med maximal vinst på 200%. Slutgiltigen lyckas även agenterna med att visa annan handelsdynamik som förväntas ske på en verklig marknad. Huvudsakligen: kluster av spreads, optimal hantering av aktielager och en minskning av spreads under simuleringarna. Detta visar att Reinforcement Learning med PPO eller DQN är relevanta val vid modellering av marknadens mikrostruktur.

Temporary closures of octopus fishing areas constitute a promising co-management measure that aims to improve local governance, food security and incomes in coastal small-scale fishing communities. Although positive social and economic outcomes of temporary closures are increasingly reported, the underlying social-ecological and ecological interactions, and their impact on closure benefits are rarely studied. This lack of systemic understanding may lead to undesired outcomes. Here, I extend an existing agent-based model of temporary closures to explore the influence of individual octopus movements on ecological outcomes and fishers’ benefits in Zanzibar. First, I conceptualized the octopus closure system by analyzing empirical qualitative data and literature. Next, I iteratively developed and tested an individual-based model extension. This extension simulates between-den movements across a hypothetical seascape and formalizes intrinsic attributes of Octopus cyanea such as movement patterns and maturity stages. I analyzed the effects of varying closure size of fishing grounds temporarily closed to illustrate potential implications for outcomes of octopus closures. Simulation results show that individual octopus movements triggered by fishing activities have noticeable impacts on octopus sizes, their spatial and temporal distribution, and fishers’ catches, particularly when considering different social groups that depend on the fishery. Scenarios with closures in place show higher mean octopus weight in closed areas in contrast to open-access areas. Mean catches for women foot-fishers are lower compared to freedivers’ catches and even slightly lower when allowing octopuses to move in response to disturbance in all scenarios. Catch rates and distribution of mature octopuses are highly sensitive to closure size revealing a social-ecological trade-off when implementing larger closures. This study demonstrates an approach to integrating individual octopus movements and interactions between fishers and octopuses in a fishery management context, and suggests that reactive movement of octopus contributes to unequal distribution of the closure benefits between different social groups. / Octopus and People In Novel Transdisciplinary Simulations (OctoPINTS project)

Progress towards sustainability requires changes in our individual and collective behaviour. Yet, our fundamental understanding of behaviour in relation to environmental change remains severely limited. In particular, little attention has been given to how individual and collective behaviours respond to, and are shaped by, non-linear environmental change (such as ‘regime shifts’) and its inherent uncertainties. The thesis makes two main contributions to the literature: 1) it provides one of the first accounts of human behaviour and collective action in relation to ecological regime shifts and associated uncertainties; and 2) extends the incipient behavioural common-pool resource literature that acknowledges social-ecological dynamics and ecological complexity. The overarching aim of this thesis is to further advance an empirically grounded understanding of human behaviour in social-ecological systems. In particular, the thesis attempts to unravel critical social-ecological factors and mechanisms for the sustainability of common-pool resources. This is especially relevant for contexts in which livelihoods can be more directly threatened by regime shifts. The following methods are applied: behavioural economic experiments in the lab (with students; Papers I and II) and in the field (with small-scale fishers from four different communities in the Colombian Caribbean; Paper III), and agent-based modelling empirically informed by a subset of the lab experiments (Paper IV). Paper I tests the effect of an endogenously driven regime shift on the emergence of cooperation and sustainable resource use. Paper II tests the effect of different risk levels of such a regime shift. The regime shift in both papers has negative consequences for the productivity of the shared resource. Paper III assesses the effect of different degrees of uncertainty about a climate-induced threshold in stock dynamics on the exploitation patterns; as well as the role of social and ecological local context. Paper IV explores critical individual-level factors and processes affecting the simultaneous emergence of collective action and sustainable resource use. Results cumulatively suggest that existing scientific knowledge indicating the potential for ecological regime shifts should be communicated to affected local communities, including the remaining uncertainties, as this information can encourage collective action for sustainable resource use. Results also highlight the critical role of ecological knowledge, knowledge-sharing, perceived ecological uncertainties, and the role local contexts play for sustainable outcomes. This thesis enriches the literature on social-ecological systems by demonstrating how a behavioural experimental approach can contribute new insights relevant for sustainability. Overall, these insights indicate that, given the opportunity and the willingness of people to come together, share knowledge, exchange ideas, and build trust, potential ecological crises can encourage collective action, and uncertainties can be turned into opportunities for dealing with change in constructive ways. This provides a hopeful outlook in the face of escalating environmental change and inherent uncertainties. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 3: Manuscript.</p>

The growth in the interdependence and complexity of socio-technical systems requires the development of tools and techniques to aid in the formulation of better policies. The efforts of this research focus towards developing methodologies and support tools for better policy design and formulation. In this thesis, a new framework and a systematic approach for the formulation of policies are proposed. Focus has been directed to the interactions between policy measures, inspired by concepts in process design and network analysis. Furthermore, we have developed an agent-based approach to create a virtual environment for the exploration and analysis of different configurations of policy measures in order to build policy packages and test the effects of changes and uncertainties while formulating policies. By developing systematic approaches for the formulation and analysis of policies it is possible to analyse different configuration alternatives in greater depth, examine more alternatives and decrease the time required for the overall analysis. Moreover, it is possible to provide real-time assessment and feedback to the domain experts on the effect of changes in the configurations. These efforts ultimately help in forming more effective policies with synergistic and reinforcing attributes while avoiding internal contradictions. This research constitutes the first step towards the development of a general family of computer-based systems that support the design of policies. The results from this research also demonstrate the usefulness of computational approaches in addressing the complexity inherent in the formulation of policies. As a proof of concept, the proposed framework and methodologies have been applied to the formulation of policies that deal with transportation issues and emission reduction, but can be extended to other domains.

Cette thèse analyse le rôle de l’apprentissage dans deux cadres de modélisation distincts. Dans le cas dunouveau modèle canonique avec apprentissage adaptatif, les caractéristiques les plus marquantes des dynamiquesd’apprentissage concernent la capacité des règles de politique monétaire à assurer la convergencevers l’équilibre en anticipations rationnelles. Le mécanisme de transmission de la politique monétaire estcelui de l’effet de substitution associé au canal de la consommation. Dans le cas d’un modèle multi-agentsqui relâche des hypothèses restrictives du nouveau modèle canonique, tout en restant structurellementproche de celui-ci, les variables agrégées évoluent à bonne distance de cet équilibre, et on observe desdynamiques nettement différentes. La politique monétaire influence les variables agrégées de manièremarginale via l’effet de revenu du canal de la consommation. En présence d’un processus d’apprentissagesocial évolutionnaire, l’économie converge vers un faible niveau d’activité économique. L’introductiond’un processus caractérisé par le fait que les agents apprennent individuellement à l’aide de leurs modèlesmentaux atténue le caractère dépressif des dynamiques d’apprentissage. Ces différences entre les deuxcadres de modélisation démontrent la difficulté de généraliser les résultats du nouveau modèle canonique. / This thesis analyses the role of learning in two different modelling frameworks. In the new canonicalmodel with adaptive learning, the most remarkable characteristics of the learning dynamics deal withthe capacity of monetary policy rules to guaranty convergence to the rational expectations equilibrium.The transmission mechanism of the monetary policy is based on the substitution effect associated to theconsumption channel. In the case of an agent-based model which relaxes some restrictive assumptionsof the new canonical model - but is endowed with a similar structure - aggregate variables evolve atsome distance from the rational expectations equilibrium. Monetary policy has a marginal impact onthe agregated variables via the wealth effect of the consumption channel. When agents learn accordingto an evolutionnary social learning process, the economy converges to regions of low economic activity.The introduction of a process where agents learn individually by using their mental models induces lessdepressive learning dynamics. These differences between the two modelling frameworks show that thegeneralisation of the results of the new canonical model is not easy to achieve.

O Dilema do Prisioneiro (DP) é o jogo mais proeminente da Teoria dos Jogos devido à emergência da cooperação entre jogadores egoístas. O comportamento de cada jogador depende da estratégia que ele adotada e do seu ganho, que é determinado em função dos parâmetros do DP (T, R, P e S) e do número z de vizinhos com que ele joga. Portanto, a estrutura espacial dos jogadores não é relevante. Em nosso trabalho, utilizamos um autômato celular unidimensional onde cada jogador pode cooperar ou desertar ao interagir, simetricamente, com seus z vizinhos mais próximos. O sistema proposto nos permitiu realizar um estudo exaustivo do espaço de parâmetros para as estratégias evolucionárias Darwiniana (EED) e a Pavloviana (EEP) e compara-las. A geometria unidimensional nos possibilita obter os mesmos resultados dos sistemas em dimensionalidade arbitrária d, além de apresentar várias vantagens em relação a elas. No sistema que propomos os efeitos de borda são menores, exige menos tempo para a execução das simulações numéricas, permite variar o valor de z e é fácil obter uma representação visual da evolução temporal do sistema. Tal visualização simplifica a compreensão das interações entre os jogadores, pois surgem padrões nos agrupamentos de cooperadores/desertores, semelhantes aos pertencentes às classes dos autômatos celulares elementares. O estudo destes padrões nos permite compreender simplesmente a emergência da cooperação ou deserção nos sistemas. A evolução temporal do sistema que adota a EED gera um diagrama de fases muito rico com a presença das fases cooperadora, desertora e caótica. Já para a EEP, obtivemos um novo resultado analítico para as transições de fase, que neste caso são: cooperadora e quasi-regular. O estudo numérico exaustivo determinou as regiões do espaço de parâmetros onde acontecem cada uma das fases, e os efeitos da auto-interação podendo assim validar os resultados teóricos. O estudo do caso particular T = 1, tradicionalmente considerado como trivial, mostrou que ele apresenta comportamentos inusitados. Nossa principal contribuição para o estudo do DP é a obtenção de um novo paradigma. A geometria unidimensional com interação de vizinhos simétricos permitiu a visualização da evolução de padrões de cooperadores e desertores, o cálculo analítico de Tc para a EEP e o estudo de T = 1 para tais sistemas. / The Prisoner Dilemma (PD) is the most prominent game of the Game Theory due to emergency of the cooperation between selfish players. The behavior of each player depends on his/her strategy and the payoff, which is determined in function of the PD parameters (T, R, P and S) and by the number z of neighbors with whom he/she plays. Therefore, the spatial structure of the players does not matter. In our work, we have used a one-dimensional cellular automaton where each player can cooperate or defect when interacting, symmetrically, with his/her z nearest neighbors. The considered system allowed us to carry out an exhaustive exploration of the parameters space for the Darwinian Evolutionary Strategy (EED) and Pavlovian (EEP) and compares them. One-dimensional geometry makes possible to us get the same results of the systems in arbitrary d dimensional networks, besides, it presents some advantages. For the system that we proposed compared to the others dimensional networks, the boundary effects are less present, it needs less time for run the numerical simulations, it allows to vary the z value and is easier to get the visual representation of the system temporal evolution. Such visualization simplifies the understanding of the interactions between the players, therefore patterns appear in the clusters of cooperator/defectors, and these patterns belong to the elementary cellular automata classes. The study of these patterns allows them to understand in an easy way the emergence of the cooperation or defection in the systems. The temporal evolution of the system that adopts the EED yields a very rich phases diagram with the presence of cooperative, defective and chaotic phases. By the other hand, for the EEP, we have got a new analytical result for the phase transitions that in this case are: quasi-regular and cooperative. The exhaustive exploration study determines the regions on the parameters space where happen each phases occurs, and the effect of the self-interaction and thus validate the theoretical results. The study of the particular case T = 1, traditionally considered as trivial one, showed that it presents unusual behaviors, that we will present. Our main contribution for the study of the DP is the attainment of a new paradigm. One-dimensional geometry with interaction of symmetrical neighbors allowed to visualizes the evolution of cooperators and defectors patterns, the analytical result for Tc for the EEP and the study of T = 1 for such systems.

O dilema do prisioneiro é geralmente visto como o ponto de partida para entender o problema da cooperação. Em comparação com o dilema do prisioneiro discreto e iterado, poucos estudos existem sobre o dilema do prisioneiro contínuo e iterado. A maioria dos trabalhos que investigaram o dilema do prisioneiro contínuo e iterado concentrou-se no período de 1990 a 2000, não obtendo resultados conclusivos sobre a melhor estratégia a ser adotada neste tipo de jogo. Duas estratégias diferentes se destacam neste tipo de dilema. A primeira é a estratégia RTS (Raise-the-Stakes) de Roberts e Sherrat (1998) que testa o terreno antes de aumentar os investimentos na relação. A segunda deriva do modelo LRS (Linear Reactive Strategies) de Wahl e Nowak (1999a). Esta última estratégia estando em equilíbrio de Nash cooperativo apresenta três características: (i) generosidade, i.e., investir o máximo possível no início da relação de cooperação; (ii) otimismo, i.e., contar com o melhor cenário para as próximas rodadas, e (iii) intransigência. Esta pesquisa tem como objetivo principal contrapor as estratégias RTS e LRS num dilema do prisioneiro contínuo e iterado, na presença e ausência de ruído, com jogadas simultâneas e alternadas e para diferentes valores do parâmetro w (probabilidade de interagir novamente). Restringimos a nossa análise a um conjunto de seis estratégias: ALLC, ALLD, TFT, RTS, LRS e RTSM. O método utilizado foi o da simulação baseada em agente (ABM) no formato de torneios, semelhante ao de Axelrod (2006), Roberts & Sherratt (1998), Nowak & Sigmund (1992) e Nowak & Sigmund (1993). Utilizamos o software Netlogo e documentamos todo o processo da concepção e construção do modelo por meio da ferramenta TRACE (TRAnsparent and Comprehensive model Evaludation). Os resultados mostram que as estratégias mais cooperativas são mais favorecidas quando o jogo consiste em jogadas alternadas ao invés de simultâneas. A estratégia RTS teve melhor desempenho em jogos simultâneos para valores intermediários de w, na presença ou ausência de ruído. Por sua vez, a estratégia LRS teve melhor desempenho nos jogos simultâneos, na presença ou ausência de ruído, ou alternados e na presença de ruído, em ambos os casos para valores grandes de w / The prisoner\'s dilemma is generally seen as the starting point for understanding the problem of cooperation. In comparison with the discreet and iterated prisoner\'s dilemma, few studies exist on the continuous iterated prisoner\'s dilemma. Most of the works that have investigated the continuous iterated prisoner\'s dilemma has concentrated in the period from 1990 to 2000, not getting conclusive results on the best strategy to be adopted in this type of game. Two different strategies stand out in this kind of dilemma. The first is the RTS strategy (Raise-the-Stakes) of Roberts and Sherrat (1998) that tests the ground before increasing investment in the relationship. The second is the model deriva LRS (Linear Reactive Strategies) de Wahl and Nowak (1999a). This last strategy being in Nash equilibrium cooperative presents three characteristics: (i) generosity, i.e., investing as much as possible at the beginning of the cooperation relationship; (ii) optimism, i.e., rely on the best scenario for the next rounds, and (iii) intransigence. This research has as main goal to reconcile opposing RTS strategies and LRS in a continuous iterated prisoner\'s dilemma, in the presence and absence of noise, with simultaneous moves and alternate and for different values of the parameter w (probability of interacting again). We restrict our analysis to a set of six strategies: ALLC, ALLD, TFT, RTS, LRS and RTSM (halfway between RTS and LRS). The method used was the agent-based simulation (ABM) in tournament format, similar to that of Axelrod (2006), Roberts (1998), Sherratt & Nowak & Sigmund (1992) and Nowak & Sigmund (1993). We use the NetLogo software and document the whole process of design and construction of the tool model TRACE (TRAnsparent and Comprehensive model Evaludation). The results show that most strategies are more favoured unions when the game consists of alternating plays rather than simultaneous. The RTS strategy had better performance in simultaneous games for intermediate values of w, in the presence or absence of noise. In turn, the IRS strategy had better performance when simultaneous games, in the presence or absence of noise, or switched, and in the presence of noise, in both cases, for large values of w

O dilema do prisioneiro é geralmente visto como o ponto de partida para entender o problema da cooperação. Em comparação com o dilema do prisioneiro discreto e iterado, poucos estudos existem sobre o dilema do prisioneiro contínuo e iterado. A maioria dos trabalhos que investigaram o dilema do prisioneiro contínuo e iterado concentrou-se no período de 1990 a 2000, não obtendo resultados conclusivos sobre a melhor estratégia a ser adotada neste tipo de jogo. Duas estratégias diferentes se destacam neste tipo de dilema. A primeira é a estratégia RTS (Raise-the-Stakes) de Roberts e Sherrat (1998) que testa o terreno antes de aumentar os investimentos na relação. A segunda deriva do modelo LRS (Linear Reactive Strategies) de Wahl e Nowak (1999a). Esta última estratégia estando em equilíbrio de Nash cooperativo apresenta três características: (i) generosidade, i.e., investir o máximo possível no início da relação de cooperação; (ii) otimismo, i.e., contar com o melhor cenário para as próximas rodadas, e (iii) intransigência. Esta pesquisa tem como objetivo principal contrapor as estratégias RTS e LRS num dilema do prisioneiro contínuo e iterado, na presença e ausência de ruído, com jogadas simultâneas e alternadas e para diferentes valores do parâmetro w (probabilidade de interagir novamente). Restringimos a nossa análise a um conjunto de seis estratégias: ALLC, ALLD, TFT, RTS, LRS e RTSM. O método utilizado foi o da simulação baseada em agente (ABM) no formato de torneios, semelhante ao de Axelrod (2006), Roberts & Sherratt (1998), Nowak & Sigmund (1992) e Nowak & Sigmund (1993). Utilizamos o software Netlogo e documentamos todo o processo da concepção e construção do modelo por meio da ferramenta TRACE (TRAnsparent and Comprehensive model Evaludation). Os resultados mostram que as estratégias mais cooperativas são mais favorecidas quando o jogo consiste em jogadas alternadas ao invés de simultâneas. A estratégia RTS teve melhor desempenho em jogos simultâneos para valores intermediários de w, na presença ou ausência de ruído. Por sua vez, a estratégia LRS teve melhor desempenho nos jogos simultâneos, na presença ou ausência de ruído, ou alternados e na presença de ruído, em ambos os casos para valores grandes de w / The prisoner\'s dilemma is generally seen as the starting point for understanding the problem of cooperation. In comparison with the discreet and iterated prisoner\'s dilemma, few studies exist on the continuous iterated prisoner\'s dilemma. Most of the works that have investigated the continuous iterated prisoner\'s dilemma has concentrated in the period from 1990 to 2000, not getting conclusive results on the best strategy to be adopted in this type of game. Two different strategies stand out in this kind of dilemma. The first is the RTS strategy (Raise-the-Stakes) of Roberts and Sherrat (1998) that tests the ground before increasing investment in the relationship. The second is the model deriva LRS (Linear Reactive Strategies) de Wahl and Nowak (1999a). This last strategy being in Nash equilibrium cooperative presents three characteristics: (i) generosity, i.e., investing as much as possible at the beginning of the cooperation relationship; (ii) optimism, i.e., rely on the best scenario for the next rounds, and (iii) intransigence. This research has as main goal to reconcile opposing RTS strategies and LRS in a continuous iterated prisoner\'s dilemma, in the presence and absence of noise, with simultaneous moves and alternate and for different values of the parameter w (probability of interacting again). We restrict our analysis to a set of six strategies: ALLC, ALLD, TFT, RTS, LRS and RTSM (halfway between RTS and LRS). The method used was the agent-based simulation (ABM) in tournament format, similar to that of Axelrod (2006), Roberts (1998), Sherratt & Nowak & Sigmund (1992) and Nowak & Sigmund (1993). We use the NetLogo software and document the whole process of design and construction of the tool model TRACE (TRAnsparent and Comprehensive model Evaludation). The results show that most strategies are more favoured unions when the game consists of alternating plays rather than simultaneous. The RTS strategy had better performance in simultaneous games for intermediate values of w, in the presence or absence of noise. In turn, the IRS strategy had better performance when simultaneous games, in the presence or absence of noise, or switched, and in the presence of noise, in both cases, for large values of w

L’agroécologie implique la conception de systèmes agricoles intégrant autant que possible les services écosystémiques. Aux produits chimiques souvent employés contre les ravageurs de cultures peut être privilégié la régulation par leurs ennemis naturels. Des résultats en écologie indiquent que des paysages agricoles dont la composition est riche en habitats semi-naturels (bois, forets, prairies, etc) les favorisent en leur fournissant abris, sites de pontes et nourriture. Il serait donc possible de mettre en place une Gestion Paysagère des Ravageurs (GPR), c’est-à-dire de concevoir et d’aménager des paysages agricoles en faveur de ces habitats afin de favoriser les ennemis naturels et le contrôle biologique. Toutefois, l’implémentation d’une telle innovation potentielle par les acteurs de ces paysages reste largement à explorer. Dans cette thèse, dans un esprit de recherche-action, nous avons pris le parti d’explorer la conception de tels paysages régulateurs de ravageurs en s’impliquant avec des acteurs locaux et scientifiques. Nous avons initié une démarche de recherche participative avec des acteurs agricoles d’une région du Tarn-et-Garonne spécialisée dans l’arboriculture fruitière, intensive en traitements chimiques. A partir de leurs représentations et de leurs connaissances nous avons cherché à déterminer quels étaient les facteurs favorables ou non à la GPR. En particulier, nous avons qualifié les conditions dans lesquelles le paysage et les ennemis naturels étaient construit socialement par ces acteurs comme des ressources pourvoyeuses de services écosystémiques de régulation. Nous avons cherché également à identifier si ces acteurs étaient liés entre eux par des dépendances pouvant nécessiter une gestion coordonnée du paysage. Nous avons exploré la possibilité de la gestion paysagère par plusieurs cycles de modélisations participatives. La thèse a ainsi : mis à jour et qualifié la diversité des modèles mentaux des acteurs locaux sur leurs stratégies de gestion des ravageurs, co-construit des modèles Bayésien participatifs afin d’explorer via des scénarios les incertitudes autour de la question de la régulation biologique des ravageurs et, enfin, réalisé la coconstruction d’un modèle multi-agents autour de le la dynamique de population du ravageur invasif Drosophila suzukii et de sa potentielle gestion paysagère. Nous avons pu ainsi déterminer qu’en l’état actuel des représentations des acteurs, qu’ils soient scientifiques ou locaux, la composition du paysage en éléments semi-naturels leur apparaît comme faiblement reliée à un service écosystémique de régulation des ravageurs, quand bien même ce paysage est souvent favorable à la biodiversité fonctionnelle. Actuellement, faute de bénéfices agricoles clairement identifiés, les acteurs impliqués sont en conséquence peu dépendants entre eux et le besoin de se coordonner pour mettre en place une GPR est faible. La plupart des agriculteurs indiquent plutôt une nette préférence pour les solutions individuelles vis-à-vis des ravageurs, par l’utilisation de pesticides et de filets protecteurs entourant les cultures. Ce focus individuel suggère qu’innover dans l’intégration de l’activité des ennemis naturels pourrait être plus aisé au niveau de la végétation naturelle des exploitations individuelles, comme peut l’être l’inter-rang des vergers. Par ailleurs, ces résultats font apparaître le besoin d’études scientifiques liant écologie et économie qui chercheraient à mesurer explicitement les bénéfices obtenus par les acteurs agricoles par le biais de paysages favorables aux ennemis naturels. Des résultats positifs de telles études seraient mobilisateurs pour de futures recherches participatives dans ce domaine. Enfin, cette thèse participative et exploratoire nous a permis également d’identifier de nouveaux terrains et questions de recherches dans le domaine de la GPR qui pourront être poursuivis. / Agroecology requires the design of farming system integrating as much as possible ecosystem services. Biological control by natural enemies may substitute commonly used pesticides. Ecology findings demonstrate that farming landscapes with a high proportion of natural habitats (woods, forests meadows, etc) favor natural enemies by providing them shelter, nesting sites and food. Landscape Pest Control (LPC), i.e. the design of farming landscapes in favor of these habitats, may be implemented to foster natural enemies and biological pest control. However, how stakeholders may design such landscapes remains unexplored. In this PhD, we followed an action-research approach and explored the design of such pest regulating landscapes together with local and scientific stakeholders. We initiated a participatory approach with agricultural stakeholders in a part of the Tarn-et-Garonne region specialized in fruit production. Our research seeks to identify the factors in favor of a LPC according to stakeholders’ representations and knowledge. In particular, we qualified the conditions under which natural enemies and the landscape are socially constructed resources providing ecosystem services. We also seek to identify if these stakeholders were linked through dependencies which may necessitate a coordinated management of the landscape. We explored the possibility of a LPC through several cycle of participatory modelling. This PhD successively established mental models of local stakeholders about their pest control strategies, co-constructed participatory Bayesian models in order to explore uncertainties surrounding LPC, and finally we co-constructed an agent-based model about the population dynamic of the invasive pest Drosophila suzukii and its potential landscape management. Our results show that, according to scientific and local stakeholder’s actual representations, the composition of the landscape in natural habitats is weakly related with pest regulation ecosystem services, even though the landscape is related with higher functional biodiversity. Nowadays, as stakeholders see little benefit, they don’t consider to be dependent to benefit from an enhanced biological control through a LPC strategy. Farmers rather mention their preference towards individual solutions such as pesticides or exclusion nets surrounding their orchards. This individual focus suggests that designing innovation favorable to natural enemies might be more relevant within farms, like focusing on the vegetation between rows of fruit trees. Besides, these results show the need for scientific studies relating economics and ecology to explicitly measure the benefits farmers could obtain from a landscape favorable to natural enemies. Positive results of such study would enhance further participatory research around LPC strategies. Finally, this participatory and exploratory research identified new sites for investigation and raised questions about the LPC which could be further looked into.

O Dilema do Prisioneiro (DP) é o jogo mais proeminente da Teoria dos Jogos devido à emergência da cooperação entre jogadores egoístas. O comportamento de cada jogador depende da estratégia que ele adotada e do seu ganho, que é determinado em função dos parâmetros do DP (T, R, P e S) e do número z de vizinhos com que ele joga. Portanto, a estrutura espacial dos jogadores não é relevante. Em nosso trabalho, utilizamos um autômato celular unidimensional onde cada jogador pode cooperar ou desertar ao interagir, simetricamente, com seus z vizinhos mais próximos. O sistema proposto nos permitiu realizar um estudo exaustivo do espaço de parâmetros para as estratégias evolucionárias Darwiniana (EED) e a Pavloviana (EEP) e compara-las. A geometria unidimensional nos possibilita obter os mesmos resultados dos sistemas em dimensionalidade arbitrária d, além de apresentar várias vantagens em relação a elas. No sistema que propomos os efeitos de borda são menores, exige menos tempo para a execução das simulações numéricas, permite variar o valor de z e é fácil obter uma representação visual da evolução temporal do sistema. Tal visualização simplifica a compreensão das interações entre os jogadores, pois surgem padrões nos agrupamentos de cooperadores/desertores, semelhantes aos pertencentes às classes dos autômatos celulares elementares. O estudo destes padrões nos permite compreender simplesmente a emergência da cooperação ou deserção nos sistemas. A evolução temporal do sistema que adota a EED gera um diagrama de fases muito rico com a presença das fases cooperadora, desertora e caótica. Já para a EEP, obtivemos um novo resultado analítico para as transições de fase, que neste caso são: cooperadora e quasi-regular. O estudo numérico exaustivo determinou as regiões do espaço de parâmetros onde acontecem cada uma das fases, e os efeitos da auto-interação podendo assim validar os resultados teóricos. O estudo do caso particular T = 1, tradicionalmente considerado como trivial, mostrou que ele apresenta comportamentos inusitados. Nossa principal contribuição para o estudo do DP é a obtenção de um novo paradigma. A geometria unidimensional com interação de vizinhos simétricos permitiu a visualização da evolução de padrões de cooperadores e desertores, o cálculo analítico de Tc para a EEP e o estudo de T = 1 para tais sistemas. / The Prisoner Dilemma (PD) is the most prominent game of the Game Theory due to emergency of the cooperation between selfish players. The behavior of each player depends on his/her strategy and the payoff, which is determined in function of the PD parameters (T, R, P and S) and by the number z of neighbors with whom he/she plays. Therefore, the spatial structure of the players does not matter. In our work, we have used a one-dimensional cellular automaton where each player can cooperate or defect when interacting, symmetrically, with his/her z nearest neighbors. The considered system allowed us to carry out an exhaustive exploration of the parameters space for the Darwinian Evolutionary Strategy (EED) and Pavlovian (EEP) and compares them. One-dimensional geometry makes possible to us get the same results of the systems in arbitrary d dimensional networks, besides, it presents some advantages. For the system that we proposed compared to the others dimensional networks, the boundary effects are less present, it needs less time for run the numerical simulations, it allows to vary the z value and is easier to get the visual representation of the system temporal evolution. Such visualization simplifies the understanding of the interactions between the players, therefore patterns appear in the clusters of cooperator/defectors, and these patterns belong to the elementary cellular automata classes. The study of these patterns allows them to understand in an easy way the emergence of the cooperation or defection in the systems. The temporal evolution of the system that adopts the EED yields a very rich phases diagram with the presence of cooperative, defective and chaotic phases. By the other hand, for the EEP, we have got a new analytical result for the phase transitions that in this case are: quasi-regular and cooperative. The exhaustive exploration study determines the regions on the parameters space where happen each phases occurs, and the effect of the self-interaction and thus validate the theoretical results. The study of the particular case T = 1, traditionally considered as trivial one, showed that it presents unusual behaviors, that we will present. Our main contribution for the study of the DP is the attainment of a new paradigm. One-dimensional geometry with interaction of symmetrical neighbors allowed to visualizes the evolution of cooperators and defectors patterns, the analytical result for Tc for the EEP and the study of T = 1 for such systems.