Artificial immune systems (AIS), biologically inspired from natural immune functions, can be reactive as well as adaptive in handling generic and varying pathogens, respectively. Researchers have used the immunological metaphors to solve science and engineering problems where unknown/unexpected scenarios are plausible. AIS can be a suitable choice for various robotic applications requiring reactive and/or deliberative control. This research aims to translate modern trends in immunology, to develop an immunity-based framework, to control a team of heterogenous robots on varying levels of task allocation and mutual interactions. The presented framework is designed to work as a multi-agent system in which safe environment is treated reactively through innate immunity, whereas unsafe situations invoke adaptive part of immune system, simultaneously. Heterogeneity is defined in terms of different sensing and/or actuation capabilities as well as in terms of different behavior-sets robot(s) possess. Task allocation ranges from primitive to advanced behaviors. Mutual interactions, on the other hand, range from simpler one-to-one interaction to mutual coordination. In this context, a new immunity-based algorithm has been developed & tested, combining innate and adaptive immunities, to regulate cell populations and corresponding maturations, along with internal health indicators, in order to effectively arbitrate behaviors/robots in a heterogenous robotic system, in environments that are dynamic and unstructured. / text

In concept, online communities allow people to access the wide range of knowledge and abilities of a heterogeneous group of users. In reality, current implementations of various online communities suffer from a lack of participation by the most qualified users. The participation of qualified users, or experts, is crucial to the social welfare and widespread adoption of such systems. This research proposes techniques for identifying the most valuable contributors to several classes of online communities, including question and answer (QA) forums and other content-oriented social networks. Once these target users are identified, content recommendation and novel quantitative incentives can be used to encourage their participation. This research represents an in-depth investigation into QA systems, while the major findings are widely applicable to online communities in general. An algorithm for recommending content in a QA forum is introduced which can route questions to the most appropriate responders. This increases the efficiency of the system and reduces the time investment of an expert responder by eliminating the need to search for potential questions to answer. This recommender is analyzed using real data captured from Yahoo! Answers. Additionally, an incentive mechanism for QA systems based on a novel class of incentives is developed. This mechanism relies on systemic rewards, or rewards that have tangible value within the framework of the online community. This research shows that human users have a strong preference for reciprocal systemic rewards over traditional rewards, and a simulation of a QA system based on an incentive that utilizes these reciprocal rewards outperforms a leading incentive mechanism according to expert participation. An architecture is developed for a QA system built upon content recommendation and this novel incentive mechanism. This research shows that it is possible to identify the most valuable contributors to an online community and motivate their participation through a novel incentive mechanism based on meaningful rewards. / text

Πολλά συστήματα πολλαπλών διαμεσολαβητών είναι εμπνευσμένα από διάφορες κοινωνίες εντόμων, τα οποία συλλογικά πετυχαίνουν διάφορους στόχους οι οποίοι είναι αδύνατο να επιτευχθούν σε ατομικό επίπεδο. Στις περισσότερες περιπτώσεις, κινητήρια δύναμη στην «συνεργασία» και τη συλλογικότητα των εντόμων είναι η στιγματική συμπεριφορά (stigmergy). Ο όρος αυτός χρησιμοποιείται στη βιολογία για να περιγράψει τον τρόπο επίδρασης αλλαγών στο περιβάλλον που προέκυψαν από μια παρελθοντική συμπεριφορά κάποιων κοινωνικών εντόμων στην συμπεριφορά ατόμων της ίδιας ομάδας. Χαρακτηριστικά παραδείγματα από τη φύση βρίσκουμε σε κάποια είδη μυρμηγκιών με τον τρόπο αναζήτησης τροφής και τη δημιουργία διαδρομών μεταξύ φωλιάς και πηγών τροφής ή την κατασκευαστική διαδικασία των τερμιτών. Αν και η έννοια αυτή είναι άρρητα συνδεδεμένη με την έκκριση μιας η περισσοτέρων χημικών ουσιών (στίγματα) για την έμμεση επικοινωνία μεταξύ ατόμων μιας κοινωνίας εντόμων, έχει εφαρμοστεί σε διαφορετικούς τομείς της επιστήμης των υπολογιστών. Αν και ένα μέρος του κλάδου της τεχνητής ζωής ασχολείται με μια ένα- προς -ένα αντιστοίχηση του έμμεσου αυτού τρόπου επικοινωνίας σε ομάδες ρομπότ που λειτουργούν στον πραγματικό κόσμο με την έκκριση κάποιας αντίστοιχης ουσίας, μεγάλο επιστημονικό ενδιαφέρον υπάρχει για την αναγωγή της έννοιας και της λειτουργίας της στιγματικής συμπεριφοράς στον ψηφιακό κόσμο: Η έννοια των ψηφιακών φερορμονών ή των στιγματικών πακέτων συναντάται, κυρίως σε αντίστοιχους αλγορίθμους δρομολόγησης πακέτων σε ένα δίκτυο κόμβων. Όσο αφορά στην ένα -προς- ένα αντιστοίχηση μηχανισμών σε συστήματα διαμεσολαβητών που λειτουργούν αναλογικά (αισθητήρες) στον πραγματικό κόσμο υπάρχουν περιπτώσεις όπου ενώ ένας στιγματικός μηχανισμός που εμφανίζεται στη φύση φαινομενικά βοηθά στην αντιμετώπιση του προβλήματος που το σύστημα καλείται να αντιμετωπίσει. Η υλοποίηση όμως ενός τέτοιου μηχανισμού μπορεί να είναι ανέφικτη λόγω τεχνικών ή / και οικονομικών λόγων. Ένας προτεινόμενος τρόπος αντιμετώπισης του προβλήματος αυτού είναι η αντιστοίχηση (προσέγγιση) ενός τέτοιου μηχανισμού με ένα μηχανισμό επικοινωνίας ο οποίος θα προσφέρει αντίστοιχα αποτελέσματα χωρίς επιπλέον ή με το μικρότερο κόστος. Για το σκοπό αυτό μπορεί να γίνει χρήση της τεχνολογίας μεταφοράς αναλογικών (π.χ ήχος, φως) ή ψηφιακών σημάτων (π.χ πακέτα δεδομένων). Πόσο στιγματικός όμως είναι μια ένας τρόπος επικοινωνίας μέσω μηνυμάτων, και ποιες είναι οι παραδοχές για κάτι τέτοιο; Μπορεί να υπάρξει αντιστοίχηση της επικοινωνίας (μέσω φερορμονών) που εμφανίζεται στη φύση με κάποιο τρόπο (ασύρματης) επικοινωνίας ο οποίος να μπορεί να εφαρμοστεί σε διαμεσολαβητές περιορισμένων δυνατοτήτων? Η αντιστοίχηση μπορεί να αξιολογηθεί με ποιοτικά κριτήρια όπως η εμφάνιση ή όχι μιας επιθυμητής συμπεριφοράς του συστήματος. Στη διπλωματική αυτή διατριβή παρουσιάζεται ένα μοντέλο ψηφιακής επικοινωνίας το οποίο θεωρητικά αντιστοιχεί στην ποιοτική στιγματική συμπεριφορά ενός συστήματος διαμεσολαβητών. Επιπλέον, εισάγονται δυο μετρήσιμα κριτήρια αξιολόγησης βάση των οποίων μπορεί να γίνει σύγκριση διαφορετικών τρόπων επικοινωνίας. Τα κριτήρια αυτά προκύπτουν από τη μοντελοποίηση μιας κοινής πλατφόρμας – συστήματος διαμεσολαβητών για ένα συγκεκριμένο σενάριο λειτουργίας. Αφού πραγματοποιήθηκαν τρεις σειρές εξομοιώσεων, προέκυψε ότι το σύστημα με χρήση ψηφιακής επικοινωνίας μπορεί να επιτύχει αυτοοργανωτική συμπεριφορά αντίστοιχη με τη συμπεριφορά όταν χρησιμοποιείται στιγματική επικοινωνία ή καμία επικοινωνία. Παρόλα αυτά, η απόδοση του συστήματος βάση των κριτηρίων αξιολόγησης δεν ήταν καλύτερη για τις περισσότερες εξομοιώσεις, κάτι που δεν ήταν θεωρητικά αναμενόμενο. Τέλος, τα αποτελέσματα των εξομοιώσεων οδηγούν σε διάφορα συμπεράσματα τα οποία πρέπει να λαμβάνονται υπόψη στη μελέτη τέτοιων συστημάτων. / Multiagent systems are inspired from insect societies, which collectively achieve different targets, each of is impossible to complete by an individual. In most cases, the driving force to insect “cooperation” and collectiveness is stigmergic behavior. This concept is used in biology to describe the way that environmental changes that occur as a result of a behavior of some social insects, affects the behavior of individuals of the same species. A prominent nature –based example is found in some ant species, where individuals use pheromones during food acquisition, creating different routes between the nest and several food sources. Another example is the termite nest building process. Stigmergy is associated to the emission of one or several chemical substances (stigmata), so as to achieve forms of indirect communication between individuals of a society, although, this concept has been used in different sections of the Computer Science. While much effort is done from the Artificial Life discipline to achieve a one-to-one equivalence of this indirect form of communication into groups of robots that operate in the real world by emitting a pheromone-alike substance, there is much interest in converting this stigmergic behavior to the digital world. The concept of digital pheromones (or stigmergic packets) is met in relative network routing algorithms. Staying on the one-to-one equivalence, there are cases and situations where a proposed stigmergic mechanism can be applied in a multiagent system, where each individual is operating using sensors and actuators inside the real world. However, the implementation of such a mechanism may be unfeasible because of technical, technological or economic reasons. A suggestion to counterattack this limitation is to approximate the stigmergic solution using a different communication mechanism, which may combine feasible, low cost implementation with corresponding to the stigmergic mechanism results. To achieve that, analog (eg light, sound) or digital (data packets) signals may be used. The question is, by using these new concepts, the mechanism of communication is classified as stigmergic and, if yes, are there any admissions? Is there any digital communication analog to the stigmergic communication which may be used to robotic and limited agents? This hypothetical equivalent can be evaluated using qualitative measures like the relevance (or absence) of a desired system behavior In this master thesis, I use a digital communication model which is theoretically assumed to be relative to the quantitative stigmergic behavior of a multiagent system. Additionally, two measurable evaluation criteria are introduced. By using these criteria, different mechanisms of communication may be compared to each other. These criteria result from the modeling of the common platform-multiagent system for a particular scenario of operation. By performing three different series of simulation, there was demonstrated that by using digital communication, the system achieves self organizing behavior relative to the behavior of the same system, using stigmergic or no form of communication. Still, the system performance (according to the introduced evaluation criteria) was not better for most cases of simulations, as it may be expected. Finally, the results lead to several conclusions that must be taken under consideration and further attention for the study of swarm intelligence based systems.

In this research, a context-aware mobile role playing game is developed to provide users with a series of story decorated quests and allows them to interact with specific real and virtual objects in the real world. The game is designed based on multi-agent architecture, which allows reusable and modular agents and makes the game much more flexible and scalable. The usefulness of the CAM-RPG is evaluated with a comprehensive experiment. The interesting findings are: (1) generated story in CAM-RPG positively influences users' attitude toward game use and increases users' perceived game usefulness; (2) users' game-playing confidence, degree of liking computer games, and attitude toward computer games significantly influence attitudes toward CAM-RPG; and (3) there is no gender difference for users' game acceptance, but users' computer game attitude, time spent playing computer games, and voluntariness of use do significantly influence users' acceptance. / 2012-02

The creation of expressive styles for digital art is one of the primary goals in non-photorealistic rendering. In this paper, we introduce a swarm-based multi-agent system that is capable of producing expressive imagery through the use of multiple digital images. At birth, agents in our system are assigned a digital image that represents their 'aesthetic ideal'. As agents move throughout a digital canvas they try to 'realize' their ideal by modifying the pixels in the digital canvas to be closer to the pixels in their aesthetic ideal. When groups of agents with different aesthetic ideals occupy the same canvas, a new image is created through the convergence of their competing aesthetic goals. We use our system to explore the concepts and techniques from a number of Modern Art movements and to create an interactive media installation. The simple implementation and effective results produced by our system makes a compelling argument for more research using swarm-based multi-agent systems for non-photorealistic rendering. / Graduate

The objective of this thesis is to develop decentralized methods for building robust multi-agent networks through self-organization. Multi-agent networks appear in a large number of natural and engineered systems, including but not limited to, biological networks, social networks, communication systems, transportation systems, power grids, and robotic swarms. Networked systems typically consist of numerous components that interact with each other to achieve some collaborative tasks such as flocking, coverage optimization, load balancing, or distributed estimation, to name a few. Multi-agent networks are often modeled via interaction graphs, where the nodes represent the agents and the edges denote direct interactions between the corresponding agents. Interaction graphs play a significant role in the overall behavior and performance of multi-agent networks. There- fore, graph theoretic analysis of networked systems has received a considerable amount of attention within the last decade. In many applications, network components are likely to face various functional or structural disturbances including, but not limited to, component failures, noise, or malicious attacks. Hence, a desirable network property is robustness, which is the ability to perform reasonably well even when the network is subjected to such perturbations. In this thesis, robustness in multi-agent networks is pursued in two parts. The first part presents a decentralized graph reconfiguration scheme for formation of robust interaction graphs. Particularly, the proposed scheme transforms any interaction graph into a random regular graph, which is robust to the perturbations of their nodes/links. The second part presents a decentralized coverage control scheme for optimal protection of networks by some mobile security resources. As such, the proposed scheme drives a group of arbitrarily deployed resources to optimal locations on a network in a decentralized fashion.

In a multi-agent system (MAS), the overall performance is greatly influenced by both the design and the control of the agents. The physical design determines the agent capabilities, and the control strategies drive the agents to pursue their objectives using the available capabilities. The objective of this thesis is to incorporate control strategies in the early conceptual design of an MAS. As such, this thesis proposes a methodology that mainly explores the interdependency between the design variables of the agents and the control strategies used by the agents. The output of the proposed methodology, i.e. the interdependency between the design variables and the control strategies, can be utilized in the requirement analysis as well as in the later design stages to optimize the overall system through some higher fidelity analyses. In this thesis, the proposed methodology is applied to a persistent multi-UAV surveillance problem, whose objective is to increase the situational awareness of a base that receives some instantaneous monitoring information from a group of UAVs. Each UAV has a limited energy capacity and a limited communication range. Accordingly, the connectivity of the communication network becomes essential for the information flow from the UAVs to the base. In long-run missions, the UAVs need to return to the base for refueling with certain frequencies depending on their endurance. Whenever a UAV leaves the surveillance area, the remaining UAVs may need relocation to mitigate the impact of its absence. In the control part of this thesis, a set of energy-aware control strategies are developed for efficient multi-UAV surveillance operations. To this end, this thesis first proposes a decentralized strategy to recover the connectivity of the communication network. Second, it presents two return policies for UAVs to achieve energy-aware persistent surveillance. In the design part of this thesis, a design space exploration is performed to investigate the overall performance by varying a set of design variables and the candidate control strategies. Overall, it is shown that a control strategy used by an MAS affects the influence of the design variables on the mission performance. Furthermore, the proposed methodology identifies the preferable pairs of design variables and control strategies through low fidelity analysis in the early design stages.

This thesis relates to the usage of trust modelling in multi-agent systems - environments in which there are interacting software agents representing various users (for example, buyers and sellers exchanging products and services in an electronic marketplace). In such applications, trust modelling may be crucial to allow one group of agents (in the e-commerce scenario, buyers) to make effective decisions about which other agents (i.e., sellers) are the most appropriate partners. A number of existing multi-agent trust models have been proposed in the literature to help buyers accurately select the most trustworthy sellers. Our contribution is to propose several modifications that can be applied to existing probabilistic multi-agent trust models. First, we examine how the accuracy of the model can be improved by limiting the network to a portion of the population consisting of the most trustworthy agents, such that the less trustworthy contributions of the remaining agents can be ignored. In particular, we explore how this can be accomplished by either setting a maximum size for a buyer's advisor network or setting a minimum trustworthiness threshold for agents to be accepted into that advisor network, and develop methods for appropriately selecting the values to limit the network size. We demonstrate that for two models, both the Personalized Trust Model (PTM) developed by Zhang as well as TRAVOS, these approaches will yield significant improvements to the accuracy of the trust model, as opposed to using an unrestricted advisor network. Our final proposed modification is to use an advisor referral system in combination with one of the network-limiting approaches. This would ensure that if a particular agent within the advisor network had not met a specified level of experience with the seller under consideration, it could be replaced by another agent that had greater experience with that seller, which should in turn allow for a more accurate modelling of the seller's trustworthiness. We present a particular approach for replacing advisors, and show that this will yield additional improvements in trust-modelling accuracy with both PTM and TRAVOS, especially if the limiting step were such that it would yield a very small advisor network. We believe that these techniques will be very useful for trust researchers seeking to improve the accuracy of their own trust models, and to that end we explain how other researchers could apply these modifications themselves, in order to identify the optimal parameters for their usage. We discuss as well the value of our proposals for identifying an "optimal" size for a social network, and the use of referral systems, for researchers in other areas of artificial intelligence.

In this work, reinforcement learning algorithms are studied with the help of potential field methods, using robosoccer simulators as test beds. Reinforcement Learning (RL) is a framework for general problem solving where an agent can learn through experience. The soccer game is selected as the problem domain a way of experimenting multi-agent team behaviors because of its popularity and complexity.

This thesis addresses the problem of learning in physical heterogeneous multi-agent systems(MAS) and the analysis of the benefits of using heterogeneous MAS with respect tohomogeneous ones. An algorithm is developed for this task; building on a previous work on stability in distributed systems by Tad Hogg and Bernardo Huberman, and combining two phenomena observed in natural systems, task partition and hierarchical dominance. This algorithm is devised for allowing agents to learn which are the best tasks to perform on the basis of each agent's skills and the contribution to the team global performance. Agents learn by interacting with the environment and other teammates, and get rewards from the result of the actions they perform. This algorithm is specially designed for problems where all robots have to co-operate and work simultaneously towards the same goal. One example of such a problem is role distribution in a team of heterogeneous robots that form a soccer team, where all members take decisions and co-operate simultaneously. Soccer offers the possibility of conducting research in MAS, where co-operation plays a very important role in a dynamical and changing environment. For these reasons and the experience of the University of Girona in this domain, soccer has been selected as the test-bed for this research. In the case of soccer, tasks are grouped by means of roles.One of the most interesting features of this algorithm is that it endows MAS with a highadaptability to changes in the environment. It allows the team to perform their tasks, whileadapting to the environment. This is studied in several cases, for changes in the environment and in the robot's body. Other features are also analysed, especially a parameter that defines the fitness (biological concept) of each agent in the system, which contributes to performance and team adaptability.The algorithm is applied later to allow agents to learn in teams of homogeneous andheterogeneous robots which roles they have to select, in order to maximise team performance. The teams are compared and the performance is evaluated in the games against three hand-coded teams and against the different homogeneous and heterogeneous teams built in this thesis. This section focuses on the analysis of performance and task partition, in order to study the benefits of heterogeneity in physical MAS.In order to study heterogeneity from a rigorous point of view, a diversity measure is developed building on the hierarchic social entropy defined by Tucker Balch. This is adapted to quantify physical diversity in robot teams. This tool presents very interesting features, as it can be used in the future to design heterogeneous teams on the basis of the knowledge on other teams.