Blockchains address trust through cryptography and consensus. Bitcoin is the first digital currency without trusted agents. Ethereum extends this technology by enabling agents on a blockchain, via smart contracts. However, a systemic trust model for smart contracts in blockchains is missing. This thesis describes the ecosystem of smart contracts as an open multi-agent system. A trust model introduces social control through deposits and review agents. Trust-related attributes are quantified in 2,561 smart contracts from GitHub. Smart contracts employ a mean of three variables and functions and one in ten has a security-related issue. Moreover, blockchains restrict computation tasks. Resolving these restrictions while maintaining trust requires verifiable computation. An algorithm for verifiable computation is developed and implemented in Solidity. It uses an arbiter enforcing the algorithm, computation services providing and verifying solutions, and a judge assessing solutions. Experiments are performed with 1000 iterations for one to six verifiers with a cheater prior probability of 30%, 50%, and 70%. The algorithm shows linear complexity for integer multiplication. The verification depends on cheater prior probability and amount of verifiers. In the experiments, six verifiers are sufficient to detect all cheaters for the three prior probabilities. / Blockchains adresserar tillit genom kryptografi och konsensus. Bitcoin är den första digitala valutan utan betrodda agenter. Ethereum utökar denna teknik genom att möjliggöra agenter i blockchain, via smart contracts. En systemisk förtroende modell för smart contracts i blockchains saknas emellertid. Denna avhandling beskriver ekosystemet för smarta kontrakt som ett öppet multi-agent system. En förtroendemodell introducerar social kontroll genom inlåning och granskningsagenter. Tillitrelaterade attribut kvantifieras i 2,561 smart contracts från GitHub. De använder ett medelvärde av tre variabler och funktioner med en av tio som har en säkerhetsre-laterad fråga. Dessutom blockchains begränsa beräkningsuppgifter. Att lösa dessa begränsningar samtidigt som du behåller förtroendet kräver kontrollerbar beräkning. En algoritm för verifierbar beräkning utvecklas och implementeras i Solidity. Den använder en arbiter som tillämpar algoritmen, computation services som tillhandahåller och verifierar lösningar och en judge som bedömer lösningar. Experiment utförs med 1000 iterationer för en till sex verifierare med en snyggare sannolikhet för 30%, 50% och 70%. Algoritmen visar linjär komplexitet för heltalsmultiplicering. Verifieringen beror på fuskans tidigare sannolikhet och antal verifierare. I experimenten är sex verifierare tillräckliga för att detektera alla cheaters för de tre tidigare sannolikheterna.

This report describes a method to control the density distribution of a large number of autonomous agents. The approach is based on the fact that there are a large number of agents in the system, and hence the time evolution of the probabilistic density distribution of agents can be described as a Markov chain. The main contribution of this paper is the synthesis of a Markov matrix which will guide the multi-agent system density to a desired steady-state density distribution, in a probabilistic sense, while satisfying some motion and safety constraints. Also, an adaptive density control method based on real time density feedback is introduced to synthesize a time-varying Markov ma- trix, which leads to better convergence to the desired density distribution. Finally, a decentralized density computation method is described. This method guarantees that all agents will have a best, and common, density estimate in a finite, with an explicit bound, number of communication updates. / text

Doctor of Philosophy / Department of Computing and Information Sciences / Scott A. DeLoach / Coalition formation is a key cooperative behavior of a system of multiple autonomous agents. When the capabilities of individual agents are not su fficient for the improvement of well-being of the individual agents or of the entire system, the agents can bene t by joining forces together in coalitions. Coalition formation is a technique for finding coalitions that are best fi tted to achieve individual or group goals. This is a computationally expensive task because often all combinations of agents have to be considered in order to find the best assignments of agents to coalitions. Previous research has therefore focused mainly on small-scale or otherwise restricted systems. In this thesis we study coalition formation in large-scale multi-agent systems. We propose an approach for coalition formation based on multi-agent simulation. This approach allows us to find coalitions in systems with thousands of agents. It also lets us modify behaviors of individual agents in order to better match a specific coalition formation application. Finally, our approach can consider both social welfare of the multi-agent system and well-being of individual self-interested agents. Power distribution systems are used to deliver electric energy from the transmission system to households. Because of the increased availability of distributed generation using renewable resources, push towards higher use of renewable energy, and increasing use of electric vehicles, the power distribution systems are undergoing signi ficant changes towards active consumers who participate in both supply and demand sides of the electricity market and the underlying power grid. In this thesis we address the ongoing change in power distribution systems by studying how the use of renewable energy can be increased with the help of coalition formation. We propose an approach that lets renewable generators, which face uncertainty in generation prediction, to form coalitions with energy stores, which on the other hand are always able to deliver the committed power. These coalitions help decrease the uncertainty of the power generation of renewable generators, consequently allowing the generators to increase their use of renewable energy while at the same time increasing their pro fits. Energy stores also bene t from participating in coalitions with renewable generators, because they receive payments from the generators for the availability of their power at speci fic time slots. We first study this problem assuming no physical constraints of the underlying power grid. Then we analyze how coalition formation of renewable generators and energy stores in a power grid with physical constraints impacts the state of the grid, and we propose agent behavior that leads to increase in use of renewable energy as well as maintains stability of the grid.

Durant ces dernières années, la congestion du trafic urbain et la pollution de l'air sont devenus d'énormes problèmes dans de nombreuses villes dans le monde. Afin de réduire cette congestion, nous pouvons investir dans l'amélioration des infrastructures de la ville. Toutefois, cette solution reste très coûteuse à entreprendre et de ne permet pas de réduire la pollution de l'air. C'est pourquoi nous travaillons sur la mobilité intelligente afin de disposer d'une meilleure utilisation de la voiture. L'application de nouvelles technologies de l'information, tels que les systèmes multi-agents appliqués au contrôle de l'information de la circulation urbaine, a permis de créer et de déployer une gestion plus intelligente du trafic comme le système DRT (transport à la demande). L'objectif des systèmes multi-agents basés sur le DRT est de gérer les taxis de manière intelligente, afin d'accroître le nombre de passagers dans chaque véhicule, et en même temps à réduire le nombre de véhicules dans les rues. Cela permettra de réduire les émissions de CO2 et la pollution de l'air causée par les véhicules, ainsi que la congestion du trafic et les coûts financiers associés. La simulation multi-agents est considérée comme un outil efficace pour les services dynamiques urbains de la circulation. Toutefois, le principal problème est de savoir comment construire un agent à base de modèle pour cette problématique. Ces travaux de recherche présente une solution basée sur les systèmes multi-agents réactifs pour la problématique du transport à la demande (DRT), qui adopte une approche multi-agent de planification urbaine en utilisant des services de contrôle qui satisfont aux principales contraintes : réduction de la période totale creuse, demandes spéciales du client, augmentation du nombre de places utilisées dans un même taxi, utilisation du nombre minimal de véhicules, etc. Dans cette thèse, nous proposons un modèle multi-agents multicouche hybride distribué pour des problématiques en temps réel. Dans la méthode proposée, un agent pour chaque véhicule trouve un ensemble de routes pour sa recherche locale, et choisit un itinéraire en coopérant avec d'autres agents se trouvant dans son domaine de planification. Nous avons examiné expérimentalement, l'efficacité de la méthode proposée. / In recent years, urban traffic congestion and air pollution have become huge problems in many cities in the world. In order to reduce congestion, we can invest in improving city infrastructures. Infrastructure improvements, however, are very costly to undertake and do not reduce air pollution. Hence we can work on intelligent mobility in order to have a more efficient car use. The application of new information technologies, such as multi-agent technologies to urban traffic information control, has made it possible to create and deploy more intelligent traffic management like DRT (Demand Responsive Transport) system. The objective of multi-agent based DRT system is to manage taxis in an intelligent way, to increase the efficient number of passengers in every vehicle, and at the same time to decrease the number of vehicles on streets. This will reduce the CO2 emissions and air pollution caused by the vehicles, as well as traffic congestion and financial costs. Multi-agent simulation has been looked as an efficient tool for urban dynamic traffic services. However, the main problem is how to build an agent-based model for it. This research presents a multi-agent based demand responsive transport (DRT) services model, which adopts a practical multi-agents planning approach for urban DRT services control that satisfies the main constraints: minimize total slack time, client’s special requests, increases taxis’ seats use ratio, and using minimum number of vehicle etc. In this thesis, we propose a multi-agent based multi-layer distributed hybrid planning model for the real-time problem. In the proposed method, an agent for each vehicle finds a set of routes by its local search, and selects a route by cooperation with other agents in its planning domain. By computational experiments, we examine the effectiveness of the proposed method. This research is supported by project “Gestion Temps Réel du Transport Collectif à la Demande” (CPER) Budgetthe French.

Ce travail de recherche est consacré à la formalisation et à la réalisation d’un processus de diagnostic pluridisplinaire. La particularité d’un tel diagnostic résulte du fait qu’il nécessite de nombreux spécialistes, chacun ayant des connaissances sur leur domaine. Le problème principal réside dans les interconnexions entre les domaines. Ces interconnexions peuvent ou non être connues et influer sur le diagnostic. Dans ce manuscrit, nous proposons de réaliser un diagnostic pluridisciplinaire l’aide d’un système multi-agents. Les agents élaborent un diagnostic local à un domaine puis, fusionnent leurs diagnostics afin d’obtenir le diagnostic pluridisciplinaire. Dans ce but, nous proposons un cadre d’argumentation et une méthode de fusion des diagnostics. Ensemble, ces deux propositions forment le modèle ANDi. / Sharing opinions among different participants is a useful and common way to build a constructive argumentation in order to solve complex problems that require the confrontation of different discipline areas. In such settings, experts build different arguments in relation to their own discipline area, then share and confront them to the other experts’ opinions. In this report we present an argumentative framework ANDi based on a multi-agent approach and Bayesian networks. In this framework, the agents support the elaboration of a global diagnostic from local ones. Local diagnostics are resulting of argumentations between group of experts from the same discipline area. We illustrate the use of this argumentation framework on the domain of fault diagnosis.

Title: Disruption of movement or cohesion of groups through individuals Author: Jiří Vejmola Department: Department of Theoretical Computer Science and Mathematical Logic Supervisor of the master thesis: Mgr. Roman Neruda, CSc., Institute of Computer Science of the ASCR, v. v. i. Abstract: Just a few of informed and like-minded individuals, guides, are needed to lead otherwise naive group. We look at some of the possible changes that can be caused by the presence of another informed individual with different intentions, an intruder. It is implied that he cannot cause anything significant under normal circumstances. To counter that and to increase his chances of success we intruduce a new parameter - credibility. We explore how it changes the overall behaviour. We show that by applying it to the intruder his influence over others increases. This in turn makes naive individuals more willing to follow him. We show that if the right conditions are met he can eventually become the one who leads the group. Keywords: multi-agent system, swarm intelligence, emergence, credibility

Disasters especially from natural phenomena are inevitable. The affected areas recover from the aftermath of a natural disaster with the support from various agents participating in humanitarian operations. There are several domains of the operation, and distributing relief aids is one. For distribution, satisfying the demand for relief aid is important since the condition of the environment is unfavorable to affected people and resources needed for the victim’s life are scarce. However, it becomes problematic when the logistic agents believed to be work properly fail to deliver the emergency goods because of the capacity loss induced from the environment after disasters. This study was proposed to address the problem of logistic agents’ unexpected incapacity which hinders scheduled distribution. The decrease in a logistic agent’s supply capability delays<br>achieving the goal of supplying required relief goods to the affected people which further endangers them. Regarding the stated problem, this study explored the importance of<br>setting the profile of logistic agents that can survive for certain duration of times. Therefore, this research defines the “survivability” and the profile of logistic agents for surviving the last mile distribution through agent based modeling and simulation. Through simulations, this study uncovered that the logistic exercise could gain survivability with the certain number and organization of logistic agents. Proper formation of organization establish the logistics’ survivability, but excessive size can threaten the survivability.

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.

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.