Designing and Programming Organizational Infrastructures for Agents situated in Artifact-based Environments

Actual trends in software development are pushing the need to face a multiplicity of diverse activities and interaction styles characterizing complex and distributed application domains, in such a way that the resulting dynamics exhibits some grade of order, i.e. in terms of evolution of the system and desired equilibrium. Autonomous agents and Multiagent Systems are argued in literature as one of the most immediate approaches for describing such a kind of challenges. Actually, agent research seems to converge towards the definition of renewed abstraction tools aimed at better capturing the new demands of open systems. Besides agents, which are assumed as autonomous entities purposing a series of design objectives, Multiagent Systems account new notions as first-class entities, aimed, above all, at modeling institutional/organizational entities, placed for normative regulation, interaction and teamwork management, as well as environmental entities, placed as resources to further support and regulate agent work. The starting point of this thesis is recognizing that both organizations and environments can be rooted in a unifying perspective. Whereas recent research in agent systems seems to account a set of diverse approaches to specifically face with at least one aspect within the above mentioned, this work aims at proposing a unifying approach where both agents and their organizations can be straightforwardly situated in properly designed working environments. In this line, this work pursues reconciliation of environments with sociality, social interaction with environment based interaction, environmental resources with organizational functionalities with the aim to smoothly integrate the various aspects of complex and situated organizations in a coherent programming approach. Rooted in Agents and Artifacts (A&A) meta-model, which has been recently introduced both in the context of agent oriented software engineering and programming, the thesis promotes the notion of Embodied Organizations, characterized by computational infrastructures attaining a seamless integration between agents, organizations and environmental entities.

Formulations and Algorithms for Routing Problems

Combinatorial Optimization is a branch of optimization that deals with the problems where the set of feasible solutions is discrete. Routing problem is a well studied branch of Combinatorial Optimization that concerns the process of deciding the best way of visiting the nodes (customers) in a network. Routing problems appear in many real world applications including: Transportation, Telephone or Electronic data Networks. During the years, many solution procedures have been introduced for the solution of different Routing problems. Some of them are based on exact approaches to solve the problems to optimality and some others are based on heuristic or metaheuristic search to find optimal or near optimal solutions. There is also a less studied method, which combines both heuristic and exact approaches to face different problems including those in the Combinatorial Optimization area. The aim of this dissertation is to develop some solution procedures based on the combination of heuristic and Integer Linear Programming (ILP) techniques for some important problems in Routing Optimization. In this approach, given an initial feasible solution to be possibly improved, the method follows a destruct-and-repair paradigm, where the given solution is randomly destroyed (i.e., customers are removed in a random way) and repaired by solving an ILP model, in an attempt to find a new improved solution.

Algoritmi esatti per il Job Shop Scheduling: approcci Mathematical Programming

In questa tesi ci occuperemo di fornire un modello MIP di base e di alcune sue varianti, realizzate allo scopo di comprenderne il comportamento ed eventualmente migliorarne l’efficienza. Le diverse varianti sono state costruite agendo in particolar modo sulla definizione di alcuni vincoli, oppure sui bound delle variabili, oppure ancora nell’obbligare il risolutore a focalizzarsi su determinate decisioni o specifiche variabili. Sono stati testati alcuni dei problemi tipici presenti in letteratura e i diversi risultati sono stati opportunamente valutati e confrontati. Tra i riferimenti per tale confronto sono stati considerati anche i risultati ottenibili tramite un modello Constraint Programming, che notoriamente produce risultati apprezzabili in ambito di schedulazione. Un ulteriore scopo della tesi è, infatti, comparare i due approcci Mathematical Programming e Constraint Programming, identificandone quindi i pregi e gli svantaggi e provandone la trasferibilità al modello raffrontato.

Theoretical and implementation aspects in the mechanization of the metatheory of programming languages

Interactive theorem provers are tools designed for the certification of formal proofs developed by means of man-machine collaboration. Formal proofs obtained in this way cover a large variety of logical theories, ranging from the branches of mainstream mathematics, to the field of software verification. The border between these two worlds is marked by results in theoretical computer science and proofs related to the metatheory of programming languages. This last field, which is an obvious application of interactive theorem proving, poses nonetheless a serious challenge to the users of such tools, due both to the particularly structured way in which these proofs are constructed, and to difficulties related to the management of notions typical of programming languages like variable binding. This thesis is composed of two parts, discussing our experience in the development of the Matita interactive theorem prover and its use in the mechanization of the metatheory of programming languages. More specifically, part I covers: - the results of our effort in providing a better framework for the development of tactics for Matita, in order to make their implementation and debugging easier, also resulting in a much clearer code; - a discussion of the implementation of two tactics, providing infrastructure for the unification of constructor forms and the inversion of inductive predicates; we point out interactions between induction and inversion and provide an advancement over the state of the art. In the second part of the thesis, we focus on aspects related to the formalization of programming languages. We describe two works of ours: - a discussion of basic issues we encountered in our formalizations of part 1A of the Poplmark challenge, where we apply the extended inversion principles we implemented for Matita; - a formalization of an algebraic logical framework, posing more complex challenges, including multiple binding and a form of hereditary substitution; this work adopts, for the encoding of binding, an extension of Masahiko Sato's canonical locally named representation we designed during our visit to the Laboratory for Foundations of Computer Science at the University of Edinburgh, under the supervision of Randy Pollack.

Algorithms for UAS insertion in civil air space

One of the most interesting challenge of the next years will be the Air Space Systems automation. This process will involve different aspects as the Air Traffic Management, the Aircrafts and Airport Operations and the Guidance and Navigation Systems. The use of UAS (Uninhabited Aerial System) for civil mission will be one of the most important steps in this automation process. In civil air space, Air Traffic Controllers (ATC) manage the air traffic ensuring that a minimum separation between the controlled aircrafts is always provided. For this purpose ATCs use several operative avoidance techniques like holding patterns or rerouting. The use of UAS in these context will require the definition of strategies for a common management of piloted and piloted air traffic that allow the UAS to self separate. As a first employment in civil air space we consider a UAS surveillance mission that consists in departing from a ground base, taking pictures over a set of mission targets and coming back to the same ground base. During all mission a set of piloted aircrafts fly in the same airspace and thus the UAS has to self separate using the ATC avoidance as anticipated. We consider two objective, the first consists in the minimization of the air traffic impact over the mission, the second consists in the minimization of the impact of the mission over the air traffic. A particular version of the well known Travelling Salesman Problem (TSP) called Time-Dependant-TSP has been studied to deal with traffic problems in big urban areas. Its basic idea consists in a cost of the route between two clients depending on the period of the day in which it is crossed. Our thesis supports that such idea can be applied to the air traffic too using a convenient time horizon compatible with aircrafts operations. The cost of a UAS sub-route will depend on the air traffic that it will meet starting such route in a specific moment and consequently on the avoidance maneuver that it will use to avoid that conflict. The conflict avoidance is a topic that has been hardly developed in past years using different approaches. In this thesis we purpose a new approach based on the use of ATC operative techniques that makes it possible both to model the UAS problem using a TDTSP framework both to use an Air Traffic Management perspective. Starting from this kind of mission, the problem of the UAS insertion in civil air space is formalized as the UAS Routing Problem (URP). For this reason we introduce a new structure called Conflict Graph that makes it possible to model the avoidance maneuvers and to define the arc cost function of the departing time. Two Integer Linear Programming formulations of the problem are proposed. The first is based on a TDTSP formulation that, unfortunately, is weaker then the TSP formulation. Thus a new formulation based on a TSP variation that uses specific penalty to model the holdings is proposed. Different algorithms are presented: exact algorithms, simple heuristics used as Upper Bounds on the number of time steps used, and metaheuristic algorithms as Genetic Algorithm and Simulated Annealing. Finally an air traffic scenario has been simulated using real air traffic data in order to test our algorithms. Graphic Tools have been used to represent the Milano Linate air space and its air traffic during different days. Such data have been provided by ENAV S.p.A (Italian Agency for Air Navigation Services).

Programming Robots with an Agent-Oriented BDI-based Control Architecture: Explorations using the JaCa and Webots Platforms

La crescente disponibilità di dispositivi meccanici e -soprattutto - elettronici le cui performance aumentano mentre il loro costo diminuisce, ha permesso al campo della robotica di compiere notevoli progressi. Tali progressi non sono stati fatti unicamente per ciò che riguarda la robotica per uso industriale, nelle catene di montaggio per esempio, ma anche per quella branca della robotica che comprende i robot autonomi domestici. Questi sistemi autonomi stanno diventando, per i suddetti motivi, sempre più pervasivi, ovvero sono immersi nello stesso ambiente nel quale vivono gli essere umani, e interagiscono con questi in maniera proattiva. Essi stanno compiendo quindi lo stesso percorso che hanno attraversato i personal computer all'incirca 30 anni fa, passando dall'essere costosi ed ingombranti mainframe a disposizione unicamente di enti di ricerca ed università, ad essere presenti all'interno di ogni abitazione, per un utilizzo non solo professionale ma anche di assistenza alle attività quotidiane o anche di intrattenimento. Per questi motivi la robotica è un campo dell'Information Technology che interessa sempre più tutti i tipi di programmatori software. Questa tesi analizza per prima cosa gli aspetti salienti della programmazione di controllori per robot autonomi (ovvero senza essere guidati da un utente), quindi, come l'approccio basato su agenti sia appropriato per la programmazione di questi sistemi. In particolare si mostrerà come un approccio ad agenti, utilizzando il linguaggio di programmazione Jason e quindi l'architettura BDI, sia una scelta significativa, dal momento che il modello sottostante a questo tipo di linguaggio è basato sul ragionamento pratico degli esseri umani (Human Practical Reasoning) e quindi è adatto alla implementazione di sistemi che agiscono in maniera autonoma. Dato che le possibilità di utilizzare un vero e proprio sistema autonomo per poter testare i controllori sono ridotte, per motivi pratici, economici e temporali, mostreremo come è facile e performante arrivare in maniera rapida ad un primo prototipo del robot tramite l'utilizzo del simulatore commerciale Webots. Il contributo portato da questa tesi include la possibilità di poter programmare un robot in maniera modulare e rapida per mezzo di poche linee di codice, in modo tale che l'aumento delle funzionalità di questo risulti un collo di bottiglia, come si verifica nella programmazione di questi sistemi tramite i classici linguaggi di programmazione imperativi. L'organizzazione di questa tesi prevede un capitolo di background nel quale vengono riportare le basi della robotica, della sua programmazione e degli strumenti atti allo scopo, un capitolo che riporta le nozioni di programmazione ad agenti, tramite il linguaggio Jason -quindi l'architettura BDI - e perché tale approccio è adatto alla programmazione di sistemi di controllo per la robotica. Successivamente viene presentata quella che è la struttura completa del nostro ambiente di lavoro software che comprende l'ambiente ad agenti e il simulatore, quindi nel successivo capitolo vengono mostrate quelle che sono le esplorazioni effettuate utilizzando Jason e un approccio classico (per mezzo di linguaggi classici), attraverso diversi casi di studio di crescente complessità; dopodiché, verrà effettuata una valutazione tra i due approcci analizzando i problemi e i vantaggi che comportano questi. Infine, la tesi terminerà con un capitolo di conclusioni e di riflessioni sulle possibili estensioni e lavori futuri.

Referee Assignment Problem Case: Italian Volleyball Championships

This thesis addresses the formulation of a referee assignment problem for the Italian Volleyball Serie A Championships. The problem has particular constraints such as a referee must be assigned to different teams in a given period of times, and the minimal/maximal level of workload for each referee is obtained by considering cost and profit in the objective function. The problem has been solved through an exact method by using an integer linear programming formulation and a clique based decomposition for improving the computing time. Extensive computational experiments on real-world instances have been performed to determine the effectiveness of the proposed approach.

Reuse Mechanisms and Concurrency: From Actors to Agent-Oriented Programming

La presente tesi è dedicata al riuso nel software. Eccettuata un'introduzione organica al tema, l'analisi è a livello dei meccanismi offerti dai linguaggi di programmazione e delle tecniche di sviluppo, con speciale attenzione rivolta al tema della concorrenza. Il primo capitolo fornisce un quadro generale nel quale il riuso del software è descritto, assieme alle ragioni che ne determinano l'importanza e ai punti cruciali relativi alla sua attuazione. Si individuano diversi livelli di riuso sulla base dell'astrazione e degli artefatti in gioco, e si sottolinea come i linguaggi contribuiscano alla riusabilità e alla realizzazione del riuso. In seguito, viene esplorato, con esempi di codice, il supporto al riuso da parte del paradigma ad oggetti, in termini di incapsulamento, ereditarietà, polimorfismo, composizione. La trattazione prosegue analizzando differenti feature – tipizzazione, interfacce, mixin, generics – offerte da vari linguaggi di programmazione, mostrando come esse intervengano sulla riusabilità dei componenti software. A chiudere il capitolo, qualche parola contestualizzata sull'inversione di controllo, la programmazione orientata agli aspetti, e il meccanismo della delega. Il secondo capitolo abbraccia il tema della concorrenza. Dopo aver introdotto l'argomento, vengono approfonditi alcuni significativi modelli di concorrenza: programmazione multi-threaded, task nel linguaggio Ada, SCOOP, modello ad Attori. Essi vengono descritti negli elementi fondamentali e ne vengono evidenziati gli aspetti cruciali in termini di contributo al riuso, con esempi di codice. Relativamente al modello ad Attori, viene presentata la sua implementazione in Scala/Akka come caso studio. Infine, viene esaminato il problema dell'inheritance anomaly, sulla base di esempi e delle tre classi principali di anomalia, e si analizza la suscettibilità del supporto di concorrenza di Scala/Akka a riscontrare tali problemi. Inoltre, in questo capitolo si nota come alcuni aspetti relativi al binomio riuso/concorrenza, tra cui il significato profondo dello stesso, non siano ancora stati adeguatamente affrontati dalla comunità informatica. Il terzo e ultimo capitolo esordisce con una panoramica dell'agent-oriented programming, prendendo il linguaggio simpAL come riferimento. In seguito, si prova ad estendere al caso degli agenti la nozione di riuso approfondita nei capitoli precedenti.

Engineering Agent-Oriented Technologies and Programming Languages for Computer Programming and Software Development

Mainstream hardware is becoming parallel, heterogeneous, and distributed on every desk, every home and in every pocket. As a consequence, in the last years software is having an epochal turn toward concurrency, distribution, interaction which is pushed by the evolution of hardware architectures and the growing of network availability. This calls for introducing further abstraction layers on top of those provided by classical mainstream programming paradigms, to tackle more effectively the new complexities that developers have to face in everyday programming. A convergence it is recognizable in the mainstream toward the adoption of the actor paradigm as a mean to unite object-oriented programming and concurrency. Nevertheless, we argue that the actor paradigm can only be considered a good starting point to provide a more comprehensive response to such a fundamental and radical change in software development. Accordingly, the main objective of this thesis is to propose Agent-Oriented Programming (AOP) as a high-level general purpose programming paradigm, natural evolution of actors and objects, introducing a further level of human-inspired concepts for programming software systems, meant to simplify the design and programming of concurrent, distributed, reactive/interactive programs. To this end, in the dissertation first we construct the required background by studying the state-of-the-art of both actor-oriented and agent-oriented programming, and then we focus on the engineering of integrated programming technologies for developing agent-based systems in their classical application domains: artificial intelligence and distributed artificial intelligence. Then, we shift the perspective moving from the development of intelligent software systems, toward general purpose software development. Using the expertise maturated during the phase of background construction, we introduce a general-purpose programming language named simpAL, which founds its roots on general principles and practices of software development, and at the same time provides an agent-oriented level of abstraction for the engineering of general purpose software systems.

A farm-level programming model to compare the atmospheric impact of conventional and organic farming

A model is developed to represent the activity of a farm using the method of linear programming. Two are the main components of the model, the balance of soil fertility and the livestock nutrition. According to the first, the farm is supposed to have a total requirement of nitrogen, which is to be accomplished either through internal sources (manure) or through external sources (fertilisers). The second component describes the animal husbandry as having a nutritional requirement which must be satisfied through the internal production of arable crops or the acquisition of feed from the market. The farmer is supposed to maximise total net income from the agricultural and the zoo-technical activities by choosing one rotation among those available for climate and acclivity. The perspective of the analysis is one of a short period: the structure of the farm is supposed to be fixed without possibility to change the allocation of permanent crops and the amount of animal husbandry. The model is integrated with an environmental module that describes the role of the farm within the carbon-nitrogen cycle. On the one hand the farm allows storing carbon through the photosynthesis of the plants and the accumulation of carbon in the soil; on the other some activities of the farm emit greenhouse gases into the atmosphere. The model is tested for some representative farms of the Emilia-Romagna region, showing to be capable to give different results for conventional and organic farming and providing first results concerning the different atmospheric impact. Relevant data about the representative farms and the feasible rotations are extracted from the FADN database, with an integration of the coefficients from the literature.

Game programming: Grafica 3d

Tesi riguardante la creazione di tutte le risorse grafiche necessarie ad un videogioco tridimensionale in prima persona con Blender e Unity3D. Gli argomenti trattati sono: prgettazione, 3D modeling, texturing e shading.

Game programming: sviluppo di un gioco

La tesi riguarda tutto il processo di progettazione di un videogioco e l'implementazione dello stesso. Gli argomenti trattati sono: Unity, Design & Gameplay e l'implementazioni del progetto.

Networks, Uncertainty, Applications and a Crusade for Optimality

In this thesis we address a collection of Network Design problems which are strongly motivated by applications from Telecommunications, Logistics and Bioinformatics. In most cases we justify the need of taking into account uncertainty in some of the problem parameters, and different Robust optimization models are used to hedge against it. Mixed integer linear programming formulations along with sophisticated algorithmic frameworks are designed, implemented and rigorously assessed for the majority of the studied problems. The obtained results yield the following observations: (i) relevant real problems can be effectively represented as (discrete) optimization problems within the framework of network design; (ii) uncertainty can be appropriately incorporated into the decision process if a suitable robust optimization model is considered; (iii) optimal, or nearly optimal, solutions can be obtained for large instances if a tailored algorithm, that exploits the structure of the problem, is designed; (iv) a systematic and rigorous experimental analysis allows to understand both, the characteristics of the obtained (robust) solutions and the behavior of the proposed algorithm.

Portfolio Approaches in Constraint Programming

Recent research has shown that the performance of a single, arbitrarily efficient algorithm can be significantly outperformed by using a portfolio of —possibly on-average slower— algorithms. Within the Constraint Programming (CP) context, a portfolio solver can be seen as a particular constraint solver that exploits the synergy between the constituent solvers of its portfolio for predicting which is (or which are) the best solver(s) to run for solving a new, unseen instance. In this thesis we examine the benefits of portfolio solvers in CP. Despite portfolio approaches have been extensively studied for Boolean Satisfiability (SAT) problems, in the more general CP field these techniques have been only marginally studied and used. We conducted this work through the investigation, the analysis and the construction of several portfolio approaches for solving both satisfaction and optimization problems. We focused in particular on sequential approaches, i.e., single-threaded portfolio solvers always running on the same core. We started from a first empirical evaluation on portfolio approaches for solving Constraint Satisfaction Problems (CSPs), and then we improved on it by introducing new data, solvers, features, algorithms, and tools. Afterwards, we addressed the more general Constraint Optimization Problems (COPs) by implementing and testing a number of models for dealing with COP portfolio solvers. Finally, we have come full circle by developing sunny-cp: a sequential CP portfolio solver that turned out to be competitive also in the MiniZinc Challenge, the reference competition for CP solvers.