Navigation of a group of autonomous agents that are needed to maintain a formation is a challenging task which has not been studied much in especially 3-D terrains. This thesis presents a novel approach to collision free path finding of multiple agents preserving a predefined formation in a 3-D terrain. The proposed method could be used in many areas like navigation of semi-automated forces (SAF) at unit level in military simulations and non player characters (NPC) in computer games. The proposed path finding algorithm first computes an optimal path from an initial point to a target point after analyzing the 3-D terrain data from which it constructs a weighted graph. Then, it employs a real-time path finding algorithm specifically designed to realize the navigation of the group from one way point to the successive one on the optimal path generated at the previous stage, preserving the formation and avoiding collision both. A software was developed to test the methods discussed here.

Multiagent systems (MAS) are systems consisting of several autonomous entities, called agents, which interact with each other to either further their own interests (competition) or in pursuit of a joint goal (cooperation). In systems composed of multiple autonomous agents, negotiation is a key form of interaction that enables groups of agents to arrive at a mutual agreement regarding some belief, goal or plan. The aim of this thesis is to develop a multiagent system that simulates the negotiation process between parties about sharing of cost overrun in international construction projects. The developed tool can be used to understand how the risks and associated costs are shared between parties under different scenarios related with the risk allocation clauses in the contract, objectives of parties and level of knowledge about actual sources of cost overrun. MAS can be utilized by decision-makers to predict potential outcomes of a negotiation process.

The complexity of the path finding and navigation problem increases when multiple agents are involved and these agents have to maintain a predefined formation while moving on a 3-D terrain. In this thesis, a novel approach for multiresolution formation representation is proposed, that allows hierarchical formations of arbitrary depth to be defined using different referencing schemes. This formation representation approach is then utilized to find and realize a collision free optimal path from an initial location to a goal location on a 3-D terrain, while preserving the formation. The proposed metod first employs a terrain analysis technique that constructs a weighted search graph from height-map data. The graph is used by an off-line search algorithm to find the shortest path. The path is realized by an on-line planner, which guides the formation along the path while avoiding collisions and maintaining the formation. The methods proposed here are easily adaptable to several application areas, especially to real time strategy games and military simulations.

Psychological studies have shown that information exchange is a key component of effective teamwork. In addition to requesting information that they need for their tasks, members of effective teams often proactively forward information that they believe other teammates require to complete their tasks. We refer to this type of communication as proactive information exchange and the formalization and implementation of this is the subject of this thesis. The important question that we are trying to answer is: under normative conditions, what types of information needs can agent teammates extract from shared plans and how can they use these information needs to proactively forward information to teammates? In the following, we make two key claims about proactive information exchange: first, agents need to be aware of the information needs of their teammates and that these information needs can be inferred from shared plans; second, agents need to be able to model the beliefs of others in order to deliver this information efficiently. To demonstrate this, we have developed an algorithm named PIEX, which, for each agent on a team, reasonably approximates the information-needs of other team members, based on analysis of a shared team plan. This algorithm transforms a team plan into an individual plan by inserting coomunicative tasks in agents' individual plans to deliver information to those agents who need it. We will incorporate a previously developed architecture for multi-agent belief reasoning. In addition to this algorithm for proactive information exchange, we have developed a formal framework to both describe scenarios in which proactive information exchange takes place and to evaluate the quality of the communication events that agents running the PIEX algorithm generate. The contributions of this work are a formal and implemented algorithm for information exchange for maintaining a shared mental model and a framework for evaluating domains in which this type of information exchange is useful.

Many biological systems are known to accomplish complex tasks in a decentralized, robust, and scalable manner - characteristics that are desirable to the coordination of engineered systems as well. Inspired by nature, we produce coordination strategies for a network of heterogenous agents and in particular, we focus on intelligent collective systems. Bottlenose dolphins and African lions are examples of intelligent collective systems since they exhibit sophisticated social behaviors and effortlessly transition between functionalities. Through preferred associations, specialized roles, and self-organization, these systems forage prey, form alliances, and maintain sustainable group sizes. In this thesis, we take a three-phased approach to bioinspiration: in the first phase, we produce agent-based models of specific social behaviors observed in nature. The goal of these models is to capture the underlying biological phenomenon, yet remain simple so that the models are amenable to analysis. In the second phase, we produce bio-inspired algorithms that are based on the simple biological models produced in the first phase. Moreover, these algorithms are developed in the context of specific coordination tasks, e.g., the multi-agent foraging task. In the final phase of this work, we tailor these algorithms to produce coordination strategies that are ready to be deployed in target applications.

A scenario where multiple entities interact with a common environment to achieve individual and common goals either co-operatively or competitively can be classified as a Multi-Agent System. In this thesis, we concentrate on the situations where the agents exhibit selfish, competitive and strategic behaviour, giving rise to interesting game theoretic and optimization problems. From a computational point of view, the presence of multiple agents introduces strategic and temporal issues, apart from enhancing the difficulty of optimization. We study the following natural mathematical models of such multi-agent problems faced in practice: a) combinatorial optimization problems with multi-agent submodular cost functions, b) combinatorial auctions with partially public valuations and c) online vertex-weighted bipartite matching and single bid budgeted allocations. We provide approximation algorithms, online algorithms and hardness of approximation results for these problems.

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