[pt] Utilizando o instrumental da teoria dos jogos evolucionários, a proposta desta dissertação é analisar as interações entre emissores de dívida e agências de avaliação de risco de crédito em um ambiente com assimetria de informação. Enquanto os primeiros precisam das notas emitidas pelas agências para acessar fontes de financiamentos no mercado, as agências são remuneradas pela prestação desse serviço. Os resultados mostram que, de forma geral, quando o número de emissores grau de investimento é pequeno, incentiva-se a adoção de uma estratégia pouco transparente de divulgação de informação por parte do emissor, aumentando a assimetria de informação. A melhor resposta das agências é utilizar uma análise básica do perfil de crédito de seus clientes. O aumento do número de emissores grau de investimento na economia incentiva o aperfeiçoamento das políticas corporativas de transparência, enquanto as agências sofisticam sua análise com o objetivo de evitar os custos de reputação associados a erros de avaliação. Empiricamente, os resultados são condizentes com a evolução da economia colombiana nas últimas décadas. A melhoria do ambiente macroeconômico desse país atraiu emissores grau de investimento incentivando a atuação de agências que utilizam metodologia de análise sofisticada e emissores que adotam uma estratégia transparente de divulgação de suas informações. / [en] Using evolutionary game theory, this work aims to analyse the interactions between debt issuers and credit rating agencies in an asymmetric information environment. While the ratings grades are required by issuers to access funding sources for their investment projects, the agency s revenue is provided by this service. The results show that when the number of investment grade issuers is small, non-transparency strategy and basic methodology of analysis dominate, worsening the information asymmetry problem. The increase in the number of investment grade issuers encourages transparency policies while the agencies adopt a sophisticated analysis, avoiding the reputation costs associated with errors. Empirically, the results are consistent with the evolution of the Colombian economy in recent decades. The country s improvement in the macroeconomic environment attracted investment grade issuers encouraging the proliferation of sophisticated rating agencies and transparent issuers.

This dissertation is an attempt at establishing a bridge between biology and physics leading naturally from the field of phase transitions in physics to the cooperative nature of living systems. We show that this aim can be realized by supplementing the current field of evolutionary game theory with a new form of self-organized temporal criticality. In the case of ordinary criticality, the units of a system choosing either cooperation or defection under the influence of the choices done by their nearest neighbors, undergo a significant change of behavior when the intensity of social influence has a critical value. At criticality, the behavior of the individual units is correlated with that of all other units, in addition to the behavior of the nearest neighbors. The spontaneous transition to criticality of this work is realized as follows: the units change their behavior (defection or cooperation) under the social influence of their nearest neighbors and update the intensity of their social influence spontaneously by the feedback they get from the payoffs of the game (environment). If units, which are selfish, get higher benefit with respect to their previous play, they increase their interest to interact with other units and vice versa. Doing this, the behavior of single units and the whole system spontaneously evolve towards criticality, thereby realizing a global behavior favoring cooperation. In the case when the interacting units are oscillators with their own periodicity, homeodynamics concerns, the individual payoff is the synchronization with the nearest neighbors (i.e., lowering the energy of the system), the spontaneous transition to criticality generates fluctuations characterized by the joint action of periodicity and crucial events of the same kind as those revealed by the current analysis of the dynamics of the brain. This result is expected to explain the efficiency of enzyme catalyzers, on the basis of a new non-equilibrium statistical physics. We argue that the results obtained apply to sociological and psychological systems as well as to elementary biological systems.

Ces travaux de recherche abordent un problème de défense anti-aérien, usuellement appelé problème d'allocation d'armes à des cibles dans la littérature. L'allocation d'armes à des cibles est un problème bien connu de la recherche opérationnelle militaire qui a rencontré un franc succès parmi la communauté des chercheurs, et qui aujourd'hui encore suscite un large engouement puisque sa propriété démontrée NP-difficile en fait un problème qui reste irrésolu. Que ce soit par des méthodes analytiques ou meta-heuristiques, le problème d'allocation d'armes à des cibles a fait l'objet de nombreuses propositions de résolution. Cependant, il est assez surprenant de voir que la modélisation proposée pour ce problème n'a guère évolué depuis qu'il est apparu pour la première fois dans la littérature en 1950. Cette modélisation peut être considérée comme obsolète aujourd'hui et ne répond plus aux exigences qui accompagnent les technologies modernes. En effet, en 60 ans le champ de bataille a complètement changé, et dans la littérature seulement un nombre limité d'études proposent de prendre en compte ces évolutions. L'étude menée dans cette thèse propose de s'intéresser aux systèmes de Commandes et Contrôles (C2) pour des applications anti-aériennes. Habituellement un système C2 est composé de senseurs, d'un centre d'opérations tactiques et d'un ou plusieurs lanceurs. Les senseurs alimentent le centre d'opérations tactiques à partir des informations qu'ils recueillent, puis, une fois ces informations reçues, le centre d'opérations tactiques va interpréter ces données afin de calculer l'atteignabilité des menaces. Enfin, un plan d'engagement qui comprend l'allocation des munitions disponibles aux cibles et une date de tir sont proposés à un opérateur humain qui aura pour mission de valider cette proposition en totalité ou partiellement, puis va procéder à l'engagement des menaces. Pour remplir cet objectif, une approche innovante et faisant l'objet d'un dépôt de brevet a été développée afin de répondre aux difficultés relatives aux problèmes d'optimisation multi-objectifs. Ensuite, un algorithme d'optimisation continue basé sur la combinaison de l'optimisation par essaim particulaires avec la théorie des jeux évolutionnaires est proposé pour optimiser les dates de tirs. L'allocation optimale, elle, est obtenue en adaptant cette méthode continue au cas discret. La preuve que l'algorithme développé est localement convergent est donnée dans cette thèse. D'autre part, l'aspect temps-réel a également fait l'objet d'une recherche attentive et l'algorithme précédemment cité a été hybridé avec les réseaux de neurones afin d'accélérer le temps de calcul des composants identifiés comme "lourds" en termes de charge de calcul. Enfin, cette étude ne se limite pas à une application de recherche opérationnelle militaire, mais inclut quelques concepts élémentaires de guidage et de navigation pour le calcul d'atteignabilité des menaces. Finalement, cette thèse permet d'identifier que les points suivants doivent faire l'objet d'une attention très particulière afin de développer un outil d'aide à la décision efficace. D'abord, la métrique d'évaluation d'un bon plan d'engagement doit être clairement analysée. Ensuite, le plan d'engagement proposé doit être stable et ne pas proposer de changements soudains qui pourraient perturber l'opérateur. Le troisième point concerne la robustesse de la solution proposée et sa capacité à faire face aux situations les plus compliquées. Quatrièmement, le temps et la charge de calcul sont des contraintes techniques qui ne peuvent pas être outrepassées. Finalement, les exigences posées lors de la préparation de mission et qui dépendent du contexte doivent faire l'objet d'une attention particulière. C'est pourquoi, l'outil d'aide à la décision proposé doit permettre un allègement significatif de la charge de travail de l'opérateur ainsi que la réduction considérable du stress lié à ce contexte / This research investigates a practical air defence problem, usually named Weapon Target Assignment (WTA) in the literature. The WTA problem is a well-known problem of military operation research that encountered a wide success in the research community, but still nowadays since it remains an unsolved problem because of its NP-hardness property. From analytical to heuristic methods, the WTA was deeply investigated and many attempts to solve this problem have been proposed. However, the proposed modelling of this problem is consistent with the 1950's technologies. Thus, the proposed modelling found in the literature can be considered as obsolete and cannot fit the requirement of the current technology advances. Indeed, the battle field dramatically changes over 60 years, and the recent literature proposes only few studies taking into account these amendments. The herein study proposes to investigate a Command & Control system (C2) in air defence applications. Usually a C2 system includes sensors, a Tactical Operation Centre (TOC) and one or more launchers. The sensors provide information about aerial tactical situation to the TOC. This TOC is in charge of evaluating the received information in order to compute the attainability of the targets, then an engagement plan that includes the assignment of the available weapons to the incoming targets and a date to fire for each assignment. This engagement plan is then proposed to one human operator in charge of accepting whole or part of this engagement plan and engage the targets following the received instructions. To achieve this goal, an innovative and patented approach to mitigate the issues related to multi-objective optimisation is proposed. Then, a continuous optimisation algorithm based on the combination of the Particle Swarm Optimisation and the Evolutionary Game Theory was proposed to determine the best dates to fire. The optimal assignment was obtained by adapting the aforementioned algorithm to the discrete case. This thesis also gives the proof that the designed algorithms are locally convergent and intensive benchmarking confirms the developed theory. In order to respect the real-time requirement, it was also devised to use the Neural Networks to lighten the identified burdensome parts of the algorithm and decrease computational time. Not limited to the military operation research field, the herein study reuse some basic concepts of missile guidance and navigation to compute the attainability of the targets. From this thesis, it can be identified that following aspects need to be carefully considered to provide an efficient decision making support to a human operator: First, clearly define what a good engagement plan is. Second, the engagement plan must be steady to avoid high rate changing in the assignments that could significantly disturb the operator. Third, the proposed engagement also must be reliable and robust to face any possible situations. Fourth, the computation time and computation load are technical constraints that cannot be overstepped. Finally, the operational constraints related to the mission context defined during a pre-mission stage must also be taken into account. Therefore, the proposed decision making support must help and significantly reduce the operator's work load in this situation of high stress and sensitive context

Cette thèse a pour sujet les effets que l’information a sur les incitations. Les trois articles fournissent et explorent des résultats lorsque l’information est la principale variable d’intérêt, est endogène, pas homogène entre les acteurs et évolue dans le temps d’une manière qui n’est pas nécessairement rationnelle. Le premier article étudie les problèmes de hold-up dans les hiérarchies verticales avec la sélection adverse montrant qu’alors que le pouvoir de négociation des travailleurs augmente, les distorsions provenant de l’asymétrie d’information disparaissent. En outre, il étudie l’effet de la scolarité et du degré d’hétérogénéité de la population de travailleurs sur la répartition du pouvoir de négociation dans les marchés réglementés. Le deuxième article assouplit l’hypothèse des croyances homogènes dans les relations principal-agent avec sélection adverse. Dans un apprentissage évolutif qui est imitatif, les principaux peuvent avoir des croyances différentes sur la répartition des types d’agents dans la population. La convergence à une croyance uniforme dépend de la taille relative de la polarisation dans les croyances. En outre, le modèle est une version d’un cobweb stable. Notre approche offre des explications pour l’alternance des périodes avec quantité oscillante et relativement stable. Le troisième article étudie la fac¸on dont le contenu informatif des politiques juridiques, comme la responsabilité stricte et négligence, en cas de soucis morales, influence la conception optimale des régimes de responsabilité. Plusieurs cas récents ont montré qu’un individu ayant causé un dommage s’expose non seulement a une sanction légale — par exemple, une amende — mais aussi a un boycott social, la désapprobation ou la stigmatisation. L’article montre que le choix d’une stratégie dépend de façon complexe de l’importance du dommage et du “coût moral”. / This thesis focuses on the effects that information has on incentives. The three papers provide and explore some results when the information is the main variable of interest, it is made endogenous, not homogeneous between actors and evolving over time in a way that is not necessarily rational. The first paper studies hold-up problems in vertical hierarchies with adverse selection showing that as the bargaining power of the worker increases, distortions coming from asymmetric information vanish. Moreover, it studies the effect of schooling and degree of heterogeneity in the workforce on the allocation of bargaining power in regulating markets. The second paper relaxes the common assumption of homogeneous beliefs in principal-agent relationships with adverse selection. In an evolutionary learning set-up, which is imitative, principals can have different beliefs about the distribution of agents’ types in the population. Convergence to a uniform belief depends on the relative size of the bias in beliefs. In addition, the set-up is a version of a stable cobweb model. Our approach offers explanations for alternating periods of oscillating and relatively steady quantity. The third paper studies how the informative content of legal policies as strict-liability and fault-based, in case of moral concerns, influences the optimal design of liability regimes. Many recent cases show that an individual found to have caused harm faces not only the possibility of a legal sanction — e.g., the damages he must pay — but also social boycott, disapproval or stigma. The paper shows that the choice of a policy depends in a complex way on the magnitude of the harm and the “moral cost”.Keywords: Bargaining, Adverse Selection, Hold-up, Evolutionary Game Theory, Heterogeneous Beliefs, Bifurcation Theory, Boycott, Law Enforcement, Strict Liability, Negligence.

La théorie des jeux évolutionnaires est un outil qui permet d’étudier l’évolution des stratégies dans une population composée d’un grand nombre d’agents qui interagissent d’une façon continue et aléatoire. Dans cette théorie, il y a deux concepts essentiels qui sont la stratégie évolutivement stable (ESS), et la dynamique de réplication. Une stratégie évolutivement stable est une stratégie, qui, si adoptée par toute la population,ne peut pas être envahie par une autre stratégie ”mutante” utilisée par une petite fraction de la population. Ce concept statique est un raffinement de l’équilibre de Nash, et il ne peut pas renseigner, par exemple, sur la durée du temps nécessaire pour que l’ESS élimine la stratégie mutante. La dynamique de réplication, originalement proposée par Hawk-Dove, est un modèle dynamique qui permet de prédire l’évolution de la fraction de chaque stratégie dans la population en fonction du temps, en réponse aux gains des stratégies et l’état de la population.Dans cette thèse, nous proposons dans une première partie une extension de la dynamique de réplication classique en y introduisant des délais hétérogènes et aléatoires.En effet, la plupart des phénomènes qui se produisent prennent un temps incertain avant d’avoir des résultats. Nous étudions l’effet de la distribution des délais sur la stabilité de l’ESS dans la dynamique de réplication et nous considérons les distributions uniforme, exponentielle, et Gamma (ou Erlang). Dans les cas des distributions uniforme et Gamma, nous trouvons la valeur critique de la moyenne à laquelle la stabilité de l’équilibre est perdue et des oscillations permanentes apparaissent. Dans le cas de la distribution exponentielle, nous montrons que la stabilité de l’équilibre ne peut être perdue,et ce pour toute valeur de la moyenne de la distribution. Par ailleurs, nous montrons que la distribution exponentielle peut affecter la stabilité de l’ESS quand une seule stratégie subit un délai aléatoire issu de cette distribution. Nous étudions également le cas où les délais sont discrets et nous trouvons une condition suffisante et indépendante des valeurs des délais pour la stabilité de l’équilibre. Dans tous les cas, nous montrons que les délais aléatoires sont moins risqués que les délais constants pour la stabilité de l’équilibre, vu que la valeur moyenne critique des délais aléatoires est toujours supérieure de celle des délais constants. En outre, nous considérons comme paramètre de bifurcation la moyenne de la distribution des délais et nous étudions les propriétés de la solution périodique qui apparait à la bifurcation de Hopf, et ce en utilisant une méthode de perturbation non linéaire. En effet, à la bifurcation de Hopf, une oscillation périodique stable apparait dont l’amplitude est fonction de la moyenne de la distribution. Nous déterminons analytiquement l’amplitude de l’oscillation au voisinage de la bifurcation de Hopf en fonction du paramètre de bifurcation et de la matrice des jeux dans les cas des distributions de Dirac, uniforme, Gamma et discrète, et nous appuyons nos résultats avec des simulations numériques. Dans une deuxième partie, nous considérons une population hétérogène composée de plusieurs communautés qui interagissent d’une manière non-uniforme. Pour chaque communauté, nous définissons les matrices des jeux et les probabilités d’interaction avec les autres communautés. Dans ce contexte, nous définissons trois ESS avec différents niveaux de stabilité contre les mutations: un ESS fort, un ESS faible et un ESS intermédiaire. Nous définissons un ESS fort comme suit: si toute la population adopte l’ESS, alors l’ESS ne peut pas être envahi par une petite fraction de mutants composée d’agents de toutes les communautés. / In this dissertation, we study evolutionary game theory which is a mathematical tool used to model and predict the evolution of strategies in a population composed of a largenumber of players. In this theory, there are two basic concepts which are the evolutionarilystable strategy (ESS) and the replicator dynamics. The ESS is originally definedas follows [1]: if all the population adopts the ESS, then no alternative strategy used bya sufficiently small fraction of the population can invade the population.The ESS is astatic concept and a refinement of a Nash equilibrium. It does not allow us, for example,to estimate the time required for the ESS to overcome the mutant strategy, neither to predictthe asymptotic distribution of strategies in the population. The replicator dynamics,originally introduced in [2], is a model of evolution of strategies according to which the growth rate of a given strategy is proportional to how well this strategy performs relative to the average pay off in the population.In the first part of this work, we propose an extended version of the replicator dynamics which takes into account heterogeneous random delays. Indeed, in many situations,the presence of uncertain delays is ubiquitous. We first consider continuous delays and we study the effect of the distribution of delays on the asymptotic stability of the mixed equilibrium in the replicator dynamics. In the case of uniform and Gamma delay distributions,we find the critical mean delay at which a Hopf bifurcation is created and the stability of the mixed equilibrium is lost. When the distribution of delays is exponential, we prove that the stability of the equilibrium cannot be affected by the delays. However, when only one strategy is delayed according to the exponential distribution,the asymptotic stability of the ESS can be lost. In all the cases, we show that the critical mean delay value is higher than that of constant delays, and thus random delays are less threatening than constant delays. In addition, we consider discrete delays and one o four results is that, when the instantaneous term is dominant, that is when the probabilityof zero delay is sufficiently high, the stability of the ESS cannot be lost.Furthermore, by taking as a bifurcation parameter the mean delay distribution, we examine the properties of the bifurcating periodic solution created near the Hopf bifurcationusing a nonlinear perturbation method. Indeed, near the Hopf bifurcation, a stable periodic oscillation appears whose amplitude depends on the value of the bifurcation parameter. We give a closed-form expression of the amplitude of the periodic solution and we validate our results with numerical simulations.In the second part, we consider an heterogeneous population composed of several communities which interact in a nonuniform manner. Each community has its own set of strategies, payoffs, and interaction probabilities. Indeed, individuals of a population have many inherent differences that favor the appearance of groups or clusters. In this scenario, we define three ESS with different levels of stability against mutations: strong,weak, and intermediate ESS, and we examine their connection to each other. A strongESS is a strategy that, when adopted by all the population, cannot be invaded by a sufficientlysmall fraction of mutants composed of agents from all the communities. Incontrast, a weak ESS is a strategy wherein each community resists invasion by a sufficientlysmall fraction of mutants in that community (local mutants). In the intermediateESS, the population adopting the ESS cannot be invaded by a small fraction of mutantswhen we consider the total fitness of the population rather than the fitness of eachcommunity separately.

Complexity underlying life is largely governed by the dynamics of interaction within and between living and nonliving entities. Evolutionary strategy games are extensively used in modelling and understanding complex behaviors in a wide range of fields including theoretical biology, social interactions, economics, politics, defense and security. Strategy games are said to distill the key elements of interactions be- tween real-world entities and organizations - one of the challenges lies in determining the mapping of complex real life situation dynamics to that of a certain game. That leads us to the two major research questions outlined below. In this thesis, we are taking evolutionary games a step further to investigate the interplay between local and global dynamics, where local dynamics are repre- sented by locally pairwise interactions among the population's players governed by the Iterated Prisoner's Dilemma game. To represent the global dynamics, two main modelling ideas are proposed, in the first model; a mixed evolutionary game is in- troduced where players are competing globally on the population level in a minority game. The interplay between local and global dynamics in this model represents the interplay between different scopes of competition between the same players. Sec- ondly, we introduce a model for studying the effect of sharing global information concerning a population of players, shedding light on how global information can alter the emerging dynamics of local interactions. Furthermore, the thesis addresses the question of whether games - with different dynamics - have unique signatures (footprints) that can be used in recognizing and differentiating among them, and whether these footprints are consistent along the evolutionary path of these games. We show here that by building winning networks between players, and determining network motifs of these winning networks, we can obtain motifs' counts signals that are sufficient to categorize and recognize the game's utility matrix used by the players. We also demonstrate that these footprints - motifs' counts - are consistent along the evolutionary path of the games, due to a hyper-cyclic behavior that exists between strategies. Finally, we show that this approach is capable of identifying whether a certain population is driven by local dynamics or both local and global dynamics using the proposed mixed game.

No description available.

本論文主要是在agent-based計算經濟體系下，利用Holland(1975)所提的遺傳演算法(genetic algorithms)作為計算工具，分別探討連鎖店賽局及寡占市場廠商價格策略的生態演化。 在連鎖店賽局的研究中，藉由agent-based計算經濟分析掠奪性定價的特性，並進一步探討參賽者價格策略的共演化(co-evolutionary)特性，及多元均衡賽局中均衡移轉的動態過程。針對賽局中不同的不確定性進行模擬，結果顯示廠商長期總合行為是否穩定，和賽局中的不確定程度有相當的關聯。另外，弱獨占者和潛在競爭者的價格策略存在著共演化特性。在此演化賽局中，Nash均衡雖非穩定均衡解，但卻最常浮現在長期總合行為中。因此，Nsah均衡對agent-based演化賽局的結果而言，相當具有參考價值。在特定的不確定程度下，長期總合行為似乎只在某些特定的Nash均衡中徘徊。這些移轉途徑並不具有對稱性，甚至移轉速度也非對稱。本研究所呈現的演化結果跳脫一般對均衡的觀念，展現出傳統理論所無法預知的共演化特性，並呈現出非對稱的吸引環。 此外，同樣在Agent-based計算經濟下探討寡占市場廠商策略生態。本研究首先闡明N參賽者囚犯兩難重複賽局和N廠商寡占賽局之間的異同，經由寡占賽局廠商償付矩陣(payoff matrix)的狀態相依馬可夫移轉矩陣( state-dependent Markov transition matrix)性質，說明N廠商寡占賽局和N參賽者囚犯兩難重複賽局的差異。其次，透過三家廠商寡占賽局的模擬實驗，以遺傳演算法建構參賽廠商的適應性行為，分別以寡占市場生態上的表現型(phenotypes)和基因型(genotype)進行分析。20次模擬結果所呈現的最終市場狀態相當分歧，有形成吸引環的三廠商寡占市場、有收斂到價格戰的三廠商寡占市場。另外也成功的模擬出三廠商寡占市場演化至雙佔市場、甚或獨占市場的過程。但是，在眾多模擬中並沒有發現持續的勾結定價狀態，反而掠奪性價格是較主要的價格策略。這些結果相對於實際經濟社會中的寡占市場，給予一個活潑生動的範例。 / Recently, genetic algorithms have been extensively applied to modeling evolution game in agent-based computational economic.　While these applications advance our understanding of evolution game, they have generated some new phenomena that have not been well treated in conventional game theory. In the first topic, we shall systemize the study of one of these new phenomena, namely, coevolutionary instability. We exemplify the basic properties of coevolutionary instability by the chain store game, which is the game frequently used to study the role of reputation effects in economics.　In addition, we point out that, while, due to uncertainty effects, Nash equilibria can no longer be stable, and they can still help us predict the dynamic process of the game.　In particular, we can see that the dynamic process of the game is well captured by a few Nash equilibria and the transition among them.　A careful study can uncover several interesting patterns and we show the impact of uncertainty on these patterns. In the second topic, the relation between the N-person IPD game and the N-person oligopoly game is rigorously addressed.　Our analytical framework shows that due to the path-dependence of the payoff matrix of the oligopoly game, the two games in general are not close in spirit.　We then further explore the significance of the path-dependence property to the rich ecology of oligopoly from an evolutionary perspective.　More precisely, we simulated the evolution of a 3-person oligopoly game, and showed that the rich ecology of oligopoly can be exhibited by modeling the adaptive behavior of oligopolists with genetic algorithms.　The emergent behavior of oligopolists are presented and analyzed.　We indicate how the path-dependence nature may shed light on the phenotypes and genotypes coming into existence.

In recent decades, it was shown that belowground competition for some plants may take form of the tragedy of the commons (TOC). In these plants, the competing neighbours invest more in root systems than would be appropriate for optimal nutrient uptake for the group and also more than they do when grown alone. However, there is also strong evidence that other species do not follow TOC, and tailor their root system to best nutrient exploitation irrespectively of competitor presence. The root investment strategy of these plants should correspond to the ideal free distribution (IFD). In my thesis I focus on two aspects:  I use game theoretical models to explore, whether those strategies can coexist within species and also whether different species can coexist if they have different strategy. From this model I draw predictions, which I test by meta-analysis.  Using Agrostis stolonifera as a model, I test assumptions on nutrient and neighbour perception, which underlie TOC and IFD models. I show that according to mathematical models, those two strategies can coexist in different species in a community, but cannot coexist within a species. Within a species, the TOC strategy should always dominate, once it appears. This can be extrapolated to macroevolutionary scale - once TOC occurs in certain clade, it should...

There is an increasing concern for the impact of humans on the environment. Traditionally, ecological models consider human influence as a constant or linearly varying parameter, whereas socioeconomic models and frameworks tend to oversimplify the ecological system. But tackling complex environmental challenges faced by our societies requires interdisciplinary approaches due to the intricate feedbacks between the socioeconomic and ecological systems involved. Thus, models of social-ecological systems couple an ecological system with a socioeconomic system to investigate their interaction in the integrated dynamical system. We define this coupling formally and apply the social-ecological approach to three ecological cases. Indeed, we focus on eutrophication in shallow freshwater lakes, which is a well-known system showing bistability between a clear water state and a turbid polluted state. We also study a model accounting for an aquifer (water stock) and a model accounting for a biotic population exhibiting bistability through an Allee effect. The socioeconomic dynamics is driven by the incentive that agents feel to act in a desirable or undesirable way. This incentive can be represented by a difference in utility, or in payoff, between two strategies that each agent can adopt: agents can cooperate and act in an environment-friendly way, or they can defect and act in an ecologically undesirable way. The agents' motivation includes such factors as the economic cost of their choice, the concern they feel for the environment and conformism to the collective attitude of the human group. Thus, the incentive to cooperate responds to the state of the ecological system and to the agents' collective opinion, and this response can be linear, nonlinear and monotonic, or non-monotonic. When investigating the mathematical form of this response, we find that monotonic non-linear responses may result in additional equilibria, cycles and basins of attraction compared to the linear case. Non-monotonic responses, such as resignation effects, may produce much more complicated nullclines such as a closed nullcline and weaken our ability to anticipate the dynamics of a social-ecological system. Regarding the modelling of the socioeconomic subsystem, the replicator dynamics and the logit best-response dynamics are widely used mathematical formulations from evolutionary game theory. There seems to be little awareness about the impact of choosing one or the other. The replicator dynamics assumes that the socioeconomic subsystem is stationary when all agents adopt the same behaviour, whereas the best-response dynamics assumes that this situation is not stationary. The replicator dynamics has formal game theoretical foundations, whereas best-response dynamics comes from psychology. Recent experiments found that the best-response dynamics explains empirical data better. We find that the two dynamics can produce a different number of equilibria as well as differences in their stability. The replicator dynamics is a limit case of the logit best-response dynamics when agents have an infinite rationality. We show that even generic social-ecological models can show multistability. In many cases, multistability allows for counterintuitive equilibria to emerge, where ecological desirability and socioeconomic desirability are not correlated. This makes generic management recommendations difficult to find and several policies with and without socioeconomic impact should be considered. Even in cases where there is a unique equilibrium, it can lose stability and give rise to sustained oscillations. We can interpret these oscillations in a way similar to the cycles found in classical predator-prey systems. In the lake pollution social-ecological model for instance, the agents' defection increases the lake pollution, which makes agents feel concerned and convince the majority to cooperate. Then, the ecological concern decreases because the lake is not polluted and the incentive to cooperate plummets, so that it becomes more advantageous for the agents to defect again. We show that the oscillations obtained when using the replicator dynamics tend to produce a make-or-break dynamics, where a random perturbation could shift the system to either full cooperation or full defection depending on its timing along the cycle. Management measures may shift the location of the social-ecological system at equilibrium, but also make attractors appear or disappear in the phase plane or change the resilience of stable steady states. The resilience of equilibria relates to basins of attraction and is especially important in the face of potential regime shifts. Sources of uncertainty that should be taken into account for the management of social-ecological systems include multistability and the possibility of counterintuitive equilibria, the wide range of possible policy measures with or without socioeconomic interventions, and the behaviour of human collectives involved, which may be described by different dynamics. Yet, uncertainty coming from the collective behaviour of agents is mitigated if they do not give up or rely on the other agents' efforts, which allows modelling to better inform decision makers.