Les cellules sont des entités complexes qui interagissent pour former des organismes supérieurs avec des comportements émergents. Pour coordonner leurs actions, les cellules utilisent des molécules messagères qui influencent le comportement de leur environnement cellulaire. Cette communication peut prendre la forme d'ordres simples ou complexes et dépendants de diverses conditions internes et externes. L'émergence de ces protocoles de communication est au centre de cette thèse ainsi que sa nature, simple ou structurée comme un langage. Un système multi-agents adaptatif (AMAS) est développé pour étudier les conditions nécessaires à l'émergence de la coopération et de la communication dans le contexte des tissus multicellulaires. A partir d'un modèle simpliste de cellule eucaryote, le comportement de l'agent cellulaire est développé et l'évolution du système global est explorée pour identifier les conditions minimales et nécessaires à l'apparition de la communication. La difficulté par rapport à d'autres systèmes multi-agents réside dans les interactions limitées entre les agents, puisque tout échange d'informations doit passer par l'environnement des cellules, en tant que molécules. A cet égard, la coordination cellulaire dépend de nombreux facteurs tels que la diffusion ou la stabilité chimique des molécules. L'un des défis de cette étude est de trouver une méthodologie de simulation qui n'introduit pas de biais vers le comportement attendu du système, à savoir la communication. Cela impose d'éviter toute méthodologie utilisant des fonctions globales de fitness comme les réseaux neuronaux ou les algorithmes génétiques. Un autre défi est l'exploration de l'espace de paramètres du système qui croît de façon exponentielle avec sa taille. Il doit être efficace et sans parti pris. Le paradigme de coopération utilisé dans le cadre d'AMAS est bien adapté à cette tâche et permet des temps de simulation raisonnables. Ce manuscrit présente l'état de l'art des simulations multicellulaires et leur utilisation potentielle dans ce contexte. Ensuite, le système AMAS est développé étape par étape pour explorer les conditions de l'émergence de la communication. A chaque étape, l'efficacité de la méthodologie est discutée et les résultats expérimentaux sont présentés pour vérifier que l'approche n'introduit pas de biais. / Cells are complex entities that interact together to form higher organisms with emergent behaviors. To coordinate their actions, cells use chemical messenger molecules that influence the behavior of their cellular environment. This communication could be in the form of simple orders or complex and dependent of various internal and external conditions. The emergence of these communication protocols is the focus of this thesis as well as its nature, simple or structured as a language. An adaptive multi-agent system (AMAS) is developed to study the necessary conditions for the emergence of cooperation and communication in the context of multicellular tissues. Starting from a simplistic model of eukaryotic cell, the cell agent behavior is developed and the global system evolution explored to identify the minimal and necessary conditions for the apparition of communication. The difficulty when compared with other multi-agent systems lies in the limited interactions between agents, since all information exchange must pass through the environment of the cells, as molecules. In this respect, cellular coordination depends on numerous factors like diffusion or chemical stability of the molecules. One challenge in this study is to be able to find a simulation methodology that does not introduce any bias towards the expected system behavior, namely communication. This imposes to avoid any methodology using global fitness functions like neural networks or genetic algorithms. Another challenge is the exploration of the parameter space of the system that grows exponentially with its size. It must be efficient and bias free. The cooperation paradigm used in the AMAS framework is well suited for this task and allows for reasonable simulation times. This work presents the state of the art in multicellular simulations and their potential use in this context. Then the AMAS system is developed step by step to explore the conditions for the emergence of communication. At each step, the efficiency of the methodology is discussed and experimental results are presented to verify that the approach is unbiased.

Le développement de Systèmes de Systèmes a pris de l'ampleur dans de nombreux domaines. Aujourd'hui, les applications complexes nécessitent que plusieurs systèmes développés indépendamment coopèrent ensemble, ce qui conduit au concept de Systèmes de Systèmes. Malgré une telle popularité, aucun consensus n'y a pas encore pu être atteint sur une définition précise de ce que sont les Systèmes de Systèmes. De plus, le nœud du problème est que la plupart des applications sont encore construites à la main et développées de manière ad hoc, c'est-à-dire, sans contraintes et sans être guidées par une structure prédéfinie. Développer un système de systèmes à la main est une tâche herculéenne pour un architecte informatique, en lui demandant de créer un entrelacement de connexions entre les systèmes composant du Système de Systèmes pour qu'ils puissent coopérer. En raison d'un tel entrelas, la complexité et le couplage serré augmentent, et l'évolution des Systèmes de Systèmes devient plus difficile, nécessitant des efforts substantiels. Pour trancher le nœud gordien auquel font face les architectes de Systèmes de Systèmes, nous proposons dans cette recherche un « framework » générique pour faciliter le développement de Systèmes de Systèmes dans le cadre de l'ingénierie des systèmes. Notre approche introduit une nouvelle architecture que nous appelons MBA pour Memory-Broker-Agent. Pour tester notre framework, nous avons construit un système de systèmes dans le domaine du développement collaboratif de logiciel. Les résultats montrent que notre approche réduit la difficulté et l'effort de développement. Sur la base de ces résultats, nous avons créé une méthode originale pour construire un système de systèmes à travers notre framework. Nous avons testé le potentiel de notre méthode ainsi que les caractéristiques génériques de notre framework, en construisant avec succès et avec plus de précision un nouveau système de systèmes dans le domaine de la Santé. / Building Systems of Systems (SoS) has gained momentum in various domains. Today, complex applications require to let several systems developed independently cooperate, leading to the moniker of SoS. Despite such popularity, no consensus has yet been reached about a precise definition of what SoS are. Moreover, the crux of the matter is that most applications are still handcrafted, being developed in an ad hoc fashion, i.e., freely and without being constrained by a predefined structure. Handcrafting SoS is an Herculean task for architects, requiring them to create an interwoven set of connections among SoS constituent systems for allowing cooperation. Because of the large number of interconnections, the complexity and tight coupling increase in SoS, and their evolution becomes more difficult, requiring substantial efforts from architects. To sever the Gordian knot faced by SoS architects, we propose in this research a generic framework for facilitating the development of SoS from a systems engineering perspective. Our approach is based on a novel architecture we call MBA for Memory-Broker-Agent. To test our framework we built an SoS for developing software collaboratively. Results show that our approach reduces the difficulty and effort for developing a SoS. Based on such results, we created an original method for building a SoS using our framework. We tested the potential of our method along with the generic features of our framework, by building a new SoS in the Health Care domain successfully and more accurately.

Management solutions for current and future Infrastructure-as-a-Service (IaaS) Data Centers (DCs) face complex challenges. First, DCs are now very large infrastructures holding hundreds of thousands if not millions of servers and applications. Second, DCs are highly heterogeneous. DC infrastructures consist of servers and network devices with different capabilities from various vendors and different generations. Cloud applications are owned by different tenants and have different characteristics and requirements. Third, most DC elements are highly dynamic. Applications can change over time. During their lifetime, their logical architectures evolve and change according to workload and resource requirements. Failures and bursty resource demand can lead to unstable states affecting a large number of services. Global and centralized approaches limit scalability and are not suitable for large dynamic DC environments with multiple tenants with different application requirements. We propose a novel fully distributed and dynamic management paradigm for highly diverse and volatile DC environments. We develop LAMA, a novel framework for managing large scale cloud infrastructures based on a multi-agent system (MAS). Provider agents collaborate to advertise and manage available resources, while app agents provide integrated and customized application management. Distributing management tasks allows LAMA to scale naturally. Integrated approach improves its efficiency. The proximity to the application and knowledge of the DC environment allow agents to quickly react to changes in performance and to pre-plan for potential failures. We implement and deploy LAMA in a testbed server cluster. We demonstrate how LAMA improves scalability of management tasks such as provisioning and monitoring. We evaluate LAMA in light of state-of-the-art open source frameworks. LAMA enables customized dynamic management strategies to multi-tier applications. These strategies can be configured to respond to failures and workload changes within the limits of the desired SLA for each application.

A qualidade do serviço oferecido por Provedores do Serviço de Internet (Internet Service Provider - ISPs) depende diretamente da quantidade de recursos disponíveis naquele momento. Nas últimas décadas, essa qualidade tem sido afetada por frequentes e intensos ataques que consomem tais recursos, como é o caso dos ataques de Negação de Serviço Distribuídos (Distributed Denial of Service - DDoS). Com o objetivo de tornar a rede dos ISPs mais resiliente aos diferentes tipos de ataques DDoS, foram desenvolvidas técnicas contra tais ataques ao longo dos últimos anos. Com o objetivo de contribuir com a melhoria de tais mecanismos, esta dissertação apresenta um método autônomo reativo para detecção e mitigação de ataques DDoS, utilizando um sistema multiagentes (SMA), em redes de ISPs. A propriedade principal do método proposto é identificar padrões de tráfego característicos de um ataque, como um grande fluxo de pacotes direcionados para um serviço ou equipamento, dentro da rede do ISP. Com os agentes posicionados nas prováveis vítimas e nos pontos da rede com maior fluxo de pacotes, o processo de mitigação inicia-se automaticamente após uma quantidade de pacotes, excedente ao tráfego padrão, passar por qualquer um dos nós monitorados. Como o tráfego entrante na rede do ISP é dinâmico, seja ele legítimo ou malicioso, a utilização de agentes tende a facilitar o processo de definição da rota de ataque, conforme mostram os resultados experimentais obtido com o sistema proposto. / The quality of service offered by the Internet Service Provider (ISP) depends directly on the amount of resources available at that time. In recent decades, this quality has been affected by the frequent and intense attacks that consume these resources, such as the Distributed Denial of Service (DDoS) attacks. In order to make the ISPs network more resilient to different types of DDoS attacks, techniques have been developed against such attacks over the past few years. Aiming to contribute to the improvement of such mechanisms, this dissertation presents a reactive autonomous method for detecting and mitigating DDoS attacks using a Multi-Agent system (MAS), in networks of ISPs. The main property of the proposed method is to identify characteristic traffic patterns of an attack, such as a large stream of packets directed to a service or equipment within the ISP network. With agents positioned on likely victims and at points of the network with the highest packet stream, the mitigation process starts automatically after a number of packets exceeding the traffic pattern, go through any of the monitored nodes. Since the incoming traffic on the network of any ISP is dynamic, whether legitimate or malicious, the using of agents tends to facilitate the process of defining the route of attack, as shown by the experimental results obtained with the proposed system.

Esta dissertação propõe uma Ontologia Funcional de Reputação para agentes. Tal ontologia representa uma parte do conhecimento científico sobre reputação provido tanto pelas Ciências Humanas quanto pelos trabalhos em Inteligência Artificial. Seu objetivo é oferecer uma perspectiva funcional para a representação e análise da reputação como mecanismo de controle social em sociedades de agentes, de forma a sustentar a implementação de modelos de reputação para agentes. A Ontologia Funcional de Reputação foi construída a partir das categorias de conhecimento da Ontologia Funcional do Direito, proposta por Valente (1995), e utiliza a categorização de conceitos definida para o mundo jurídico para a representação do mundo social. A ontologia foi codificada em OWL DL, uma linguagem formal baseada em lógica descritiva. Uma vez construída a ontologia, os conceitos utilizados por diversos modelos e sistemas de reputação foram utilizados na sua avaliação. A utilização de um motor de inferência permitiu comparar estes conceitos, representados por meio de classes OWL, com as classes da ontologia. Tal comparação permite avaliar, de modo preliminar, a adequação do uso da Ontologia Funcional de Reputação como uma possível interlingua entre diversos agentes heterogêneos, cada qual utilizando um modelo de reputação diferente, que necessitam interoperar. / This work presents a Functional Ontology of Reputation for agents. This ontology represents the broad knowledge about reputation produced in some areas of interest such as Social Sciences and Artificial Intelligence. Its goal is to provide a functional perspective both to represent and analyze reputation as a social control mechanism for agent’s societies, in order to support the implementation of reputation model for agents. The Functional Ontology of Reputation employs the primitive categories of knowledge used in the Functional Ontology of Law proposed by Valente (1995). The idea is that the concepts of the legal world can be used to model the social world, through the extension of the concept of legal rule to social norm and the internalization of social control mechanisms in the agent's mind, so far externalized in legal institutions. The Functional Ontology of Reputation contains five main categories that have been borrowed from or inspired by the Functional Ontology of Law: Reputative Knowledge, Responsibility Knowledge, Normative Knowledge, World Knowledge and Common Sense Knowledge.As in the Functional Ontology of Law, the distinction among the categories of the reputation ontology are accomplished according to a functional perspective, in which each component of the reputation system, embedded in the social system, exists to perform a specific function in the effort to achieve social objectives, such as trust, reciprocity and social cooperation. The Functional Ontology of Reputation was implemented in OWL, a description logic language. This ontology was evaluated by using several concepts related to reputation, included in different reputation models and reputation systems. These concepts were defined as OWL classes and a reasoner was used in order to produce the comparison between these concepts and the ontology classes. This comparison allows evaluating, in a preliminary way, the Functional Ontology of Reputation utilization as a possible interlingua between several heterogeneous agents that need to interoperate, despite the utilization of different reputation model.

In direct reference to the saying “time is money”, nowadays scenario simulations play a key role in the tasks people perform. Optimizing the time length of tasks and synchronizing them properly is essential to increased profits in any line of business. In this thesis the Bergkvist-Insjön sawmill yard process will be computer simulated. As the number of trucks arriving at the sawmill is unknown, the unexpected arrival of trucks would produce a high pressure on internal resources and handling operations. The aim of this paper is to optimize the usage of the resources in the Bergkvist-Insjön sawmill, by running three different scenarios built based on the real system simulation. Scenario number three, in which a log stacker only has the tasks to unload the trucks and supply the measurement station, has been found most efficient. In the simulation of this scenario, the number of logs processed by the sawmill is the highest one. Also, the time spent by the log stackers between their tasks is the shortest one from all scenarios. The results of this thesis revealed that the most efficient improvement of the sawmill yard would be gained by a different tasks’ priority for the operating log stackers.

A qualidade do serviço oferecido por Provedores do Serviço de Internet (Internet Service Provider - ISPs) depende diretamente da quantidade de recursos disponíveis naquele momento. Nas últimas décadas, essa qualidade tem sido afetada por frequentes e intensos ataques que consomem tais recursos, como é o caso dos ataques de Negação de Serviço Distribuídos (Distributed Denial of Service - DDoS). Com o objetivo de tornar a rede dos ISPs mais resiliente aos diferentes tipos de ataques DDoS, foram desenvolvidas técnicas contra tais ataques ao longo dos últimos anos. Com o objetivo de contribuir com a melhoria de tais mecanismos, esta dissertação apresenta um método autônomo reativo para detecção e mitigação de ataques DDoS, utilizando um sistema multiagentes (SMA), em redes de ISPs. A propriedade principal do método proposto é identificar padrões de tráfego característicos de um ataque, como um grande fluxo de pacotes direcionados para um serviço ou equipamento, dentro da rede do ISP. Com os agentes posicionados nas prováveis vítimas e nos pontos da rede com maior fluxo de pacotes, o processo de mitigação inicia-se automaticamente após uma quantidade de pacotes, excedente ao tráfego padrão, passar por qualquer um dos nós monitorados. Como o tráfego entrante na rede do ISP é dinâmico, seja ele legítimo ou malicioso, a utilização de agentes tende a facilitar o processo de definição da rota de ataque, conforme mostram os resultados experimentais obtido com o sistema proposto. / The quality of service offered by the Internet Service Provider (ISP) depends directly on the amount of resources available at that time. In recent decades, this quality has been affected by the frequent and intense attacks that consume these resources, such as the Distributed Denial of Service (DDoS) attacks. In order to make the ISPs network more resilient to different types of DDoS attacks, techniques have been developed against such attacks over the past few years. Aiming to contribute to the improvement of such mechanisms, this dissertation presents a reactive autonomous method for detecting and mitigating DDoS attacks using a Multi-Agent system (MAS), in networks of ISPs. The main property of the proposed method is to identify characteristic traffic patterns of an attack, such as a large stream of packets directed to a service or equipment within the ISP network. With agents positioned on likely victims and at points of the network with the highest packet stream, the mitigation process starts automatically after a number of packets exceeding the traffic pattern, go through any of the monitored nodes. Since the incoming traffic on the network of any ISP is dynamic, whether legitimate or malicious, the using of agents tends to facilitate the process of defining the route of attack, as shown by the experimental results obtained with the proposed system.

Le Conseil Général de la Gironde (CG33) est une collectivité territoriale qui met en oeuvre les politiques décidées par des élus. L’une de ses missions fondamentales est l’induction de comportements auprès des citoyens, des acteurs économiques et institutionnels. Citons par exemple la concrétisation, par l’intermédiaire de la réalisation de projets, des politiques publiques autour des thématiques du développement Durable (DD). Un constat issu des retours d’expérience s’impose : les projets mis en oeuvre au CG 33 sont de plus en plus complexes. Ils requièrent la collaboration de nombreux acteurs publics et privés qui se connaissent mal. Les démarches territoriales de DD nécessitent l’articulation de compétences spécifiques et interdépendantes, qui n’existent pas chez un acteur unique. Ces constats sont généralisables, quel que soit le secteur d’activité professionnelle. La connaissance, l’identification et le partage optimal de compétences est au coeur même de la réussite de projets. La problématique consiste à répondre aux attentes de tout maître d’oeuvre qui doit être capable de définir un projet, d’identifier les compétences qui le composent, les acteurs capables d’exercer ces compétences, puis finalement d’évaluer à postériori la réussite globale du projet. Définir la liste des compétences n’est pas toujours aisé puisqu’elles évoluent au fil du temps. Elles peuvent, par exemple, se transformer suite à l’arrivée d’évolutions techniques. Elles peuvent également disparaitre si elles sont remplacées ou bien finalement non utilisées. Un système optimal se doit donc d’être dynamique lors de la constitution des projets au fil du temps, dans le but de coller au plus prêt de la réalité du contexte dans lequel le système est utilisé. Nous voyons bien ici que la Compétence(et non l’acteur) est l’élément fondamental du système.Une réponse dite « classique » pourrait consister à réaliser simplement une base de données où les compétences et acteurs seraient des objets statiques. Cette solution ne répondant pas à notre souhait de dynamisme. Nous proposons plutôt un système informatique collaboratif, accessible en ligne, dans lequel nous définissions des « agents compétence » (AC), dynamiques et apprenants, qui évoluent au sein d’une architecture de type multi-agents. Chaque AC y est unique, bien qu’il puisse être incarné sur le terrain par plusieurs acteurs humains. Il possède une « vie propre », des moyens d'actions multiples et multi-localisés (réparti sur plusieurs acteurs physiques). Tout AC dispose de mécanismes de perception de son environnement, de communication avec les autres ACs. Il utilise de ressources (telles que les acteurs humains) et vise à réaliser 4buts principaux :1. Constituer sa propre définition (liste des compétences élémentaires) 2. Restituer une liste d’acteurs humains capables de le concrétiser sur le terrain3. Etablir des relations avec d’autres ACs afin d’optimiser la constitution des projets4. Se porter spontanément candidat à une participation à de nouveaux projets. Nos ACs ont également un « cycle de vie » décliné en 3 « âges » (enfance, adolescence et maturité). Chacun d’eux correspond à un niveau d’autonomie particulier. Notre SMA est de type «évènementiel ». Les agents y évoluent grâce aux interactions avec les194 utilisateurs humains du système. Un « modèle comportemental » dédié et évolutif est proposé dans le but d’optimiser leur dynamisme et de stimuler leur apprentissage. / In France, the “Conseil Général de la Gironde” is a local authority that promotes various sustainable development policies and practices. One of its missions is to coordinate and stimulate public and private partnerships in the framework of green building projects.Whatever the sector of professional activities and the thematic addressed, the concrete projects’ feedbacks show all the complexity to succeed in managing efficiently the collaboration of involved actors. Indeed, each of them has only a partial knowledge ofthe others’ skills. To answer to the problematic, and in order to improve the management of the projects, we propose an online collaborative tool that allows actors to share skills. According to the “Multi-Agent” theory, "skill agents" have been defined.The key idea is to consider that a skill is an agent of the system, and the actors are only its resources.Skill agents are dynamic and autonomous, have learning abilities, and have their ownlife cycle. They pursue four main goals: building their own definition, identifying actorswho can concretize them across projects, setting up links with other skill agents, and beeing candidates to new projects. Skill agents interact with human actors to stimulate their cooperation.This work shows that our model is appropriate for complex collaborative projects,giving results in various areas. For example, a case study based on the selection of players to form a rugby team has been given.

Le travail présenté dans cette thèse définit une nouvelle approche pour la modélisation et la conceptualisation des processus métiers dans les entreprises afin de construire des outils logiciels d'assistance intelligents qui prennent en charge ces processus. L'approche proposée définit une ontologie dédiée à l'étude des organisations, nommée K-CRIO. Elle est décrite à l'aide du langage de représentation des connaissances OWL. Afin d'illustrer nos travaux, un système d'assistance a été implanté sur la base des résultats issus de la modélisation et de la conceptualisation d'un processus métier spécifique avec l'ontologie K-CRIO. Ce système prend la forme d'une application Web qui intègre et exploite pleinement les avantages des systèmes multiagents. L'ontologie K-CRIO est une ontologie dédiée à l'étude des organisations et à l'analyse organisationnelle des processus métiers qu'elles mettent en oeuvre. Plus précisément, elle est utilisée pour comprendre, analyser et raisonner sur ces organisations. Les organisations visées sont celles composées d'acteurs humains impliqués tout au long de la conception de produits et, pour ce faire, organisés selon un processus métier. L'éventail de ce type d'organisations est assez large. Nous avons donc limité notre étude aux organisations qui produisent des logiciels comme objectif final du processus. Dans ce contexte, l'ontologie K-CRIO peut être utilisée pour modéliser la structure organisationnelle du processus et les activités qui en résultent. Cette ontologie peut ensuite être exploitée afin de concevoir des outils d'assistance à la mise en oeuvre des processus ciblés au sein des organisations décrites. Plus précisément, l'ontologie fournit des moyens de raisonnement, d'annotation des ressources, et de suivi des processus de conception, permettant des recherches et de proposer pro-activement des conseils et des contenus appropriés. Afin d'illustrer l'utilisation de K-CRIO, nous appliquons K-CRIO sur deux processus différents: le modèle en cascade et la méthodologie Scrum. Ces exemples sont des processus de développement de logiciels classiques. En outre, pour le processus Scrum, qui est un processus agile de développement de logiciel, largement utilisé dans les entreprises de logiciels, nous avons conçu et développé un outil d'assistance intelligent. Cet outil contribue principalement à aider les Scrum Masters en leur fournissant des indicateurs pour les assister dans leurs prises de décisions ainsi que par la constitution d'une base de connaissances sur les activités / The work presented in this PhD thesis defines a new approach for the modeling and the conceptualization of enterprise business processes in the perspective of building intelligent assistance software tools to support these processes. The proposed approach defines an organizational ontology, named K-CRIO. Its description is based on the Ontology Web Language. To illustrate our work, an intelligent assistance system has been designed and implemented according to the result from the modeling and conceptualization of a specific business process with the K-CRIO Ontology. It is a web-based application that integrates and takes full advantage of multi-agent systems.The K-CRIO Ontology is an Ontology dedicated to the study of organizations and the analysis of business processes adopting an organizational point of view. Specifically, it is used to understand, analyze and reason about organizations and the processes they implement. The targeted organizations are those composed of entities involved throughout products' design and, to do so, following a defined business process. The range of this type of organizations is quite wide. We have thus limited our study to organizations that produce software as the final process goal, specifically IT enterprises delivering software products or services. In this context, the K-CRIO ontology could be used to model structure of the considered organizations and model human activities appearing in their business processes. This ontology could be used to support process assistance within the described organizations. More specifically, the ontology could provide means for reasoning, annotating resources, monitoring design processes, enabling searches and pro-actively proposing tips and proper content. In order to illustrate the usage of K-CRIO, we apply K-CRIO on two different processes: the Waterfall Model and the Scrum methodology. These examples are both classical software-development processes. Moreover, for Scrum, the famous agile software-development process widely used in software enterprises, we have designed and developed an intelligent assistance tool. This tool mainly helps Scrum Masters to make decision by monitoring Scrum project teams' activities within their various projects and collecting knowledge about these activities.

對於現有文獻中討論的預測市場模型，嘗試加入風險與聲譽變數，觀察與分析其成效，並參考文獻中的代理人系統實驗方法，對論文中相關部分進行修正、設計並模擬之預測市場模型。 / In this research, we proposed two variables that could be incorporated with prediction markets: Reputation and Risk. Instead of attracting new players, The reputation system could stop losing bankrupted player, Player willing to help bankrupted player will gain reputation, and bankrupted player will lose reputation. Previous works suggest longshot bias is related to the risk-neutrality of players. Our approach is to experiment dierent risk distribution. We observe the impact of these variables in an agent-based model of prediction markets. We use zero-intelligence agents, where human qualities such as maximizing prot, learning or obeserving are missing. We further discuss the result, and the impact of risk and reputation.