ALMA MATER STUDIORUM — UNIVERSITA` DI BOLOGNA DISI - Dipartimento di Informatica: Scienza e Ingegneria Dottorato in Informatica Ciclo XXVIII Settore Concorsuale: 09/H1 Settore Disciplinare: ING-INF/05 COORDINATION ISSUES IN COMPLEX SOCIO-TECHNICAL SYSTEMS: SELF-ORGANISATION OF KNOWLEDGE IN MoK Candidato Dott. Ing. STEFANO MARIANI Supervisore Chiar.mo Prof. Ing. ANDREA OMICINI Tutor Chiar.mo Prof. Ing. ANDREA OMICINI Coordinatore Chiar.mo Prof. Ing. PAOLO CIACCIA FINAL EXAMINATION YEAR 2016 iii To my beloved wife, Alice To our beloved daughter, Asia Acknowledgements This thesis belongs not only to me, but also to all the researchers and professionals I had the pleasure to work with during this three-years effort. I wish to thank Prof. Andrea Omicini for his supervision during my PhD: he is a constant and endless source of invaluably precious suggestions, criticism, and inspiration, as well as a wonderful person to share random thoughts with. A special mention goes to Prof. Di Marzo-Serugendo and Prof. Yee-King, the reviews whose comments helped in shaping the final version of this thesis, and to Prof. Michela Milano, Prof. Fabio Vitali, and Prof. Enrico Denti, the members of my internal committee which evaluated progress of the PhD research efforts. I wish to thank Prof. Mirko Viroli and Prof. Alessandro Ricci for sharing with me many enlightening discussions, as well as a many launch breaks: they may be unaware of this, but their research work has always been a reference for me. I wish to thank Danilo Pianini, Sara Montagna, and Andrea Santi for the wonderful time we had in the APICe lab, and for all the precious discussions we shared. A special mention goes to Roberta Calegari for being so efficient in fixing tuProlog issues for the benefit of TuCSoN. I wish to thank Prof. Schahram Dustdar, Prof. Hong-Linh Truong, Geor- giana Copil, and all the distributed systems group of TU Wien, for hosting me during my period abroad: I learnt many things by working with them, and gained a broader perspective on my own work. A special mention goes to Alessio Gambi for making me feel at home while there. I wish to thank all the brilliant students I had the pleasure to super- vise for their thesis and graduate projects, from whom I have learnt as much as I have taught. A special mention goes to Michele Pratiffi, Mat- tia Occhiuto, Giulio Crestani, Gianluca Spadazzi, Giacomo Dradi, Luca Santonastasi, Matteo Fattori, Matteo Francia, Giovanni Ciatto, Michele Bombardi, Lorenzo Forcellini Reffi. iv Last, but not least, I owe everything I have to my family: my wife Alice constantly supports me and helps me in every single important decision, and our daughter Asia has been fundamental to refresh my energies when the work to do was just too much. My parents, too, always supported me, and constantly demonstrated their care and pride about my research work, while my brother has been always available for taking a break from work. Stefano Mariani, March 30, 2016 Contents 1 About this Thesis 1 1.1 Organisation of Chapters . .2 1.2 List of Publications . .5 I Coordination Issues in Complex Socio-technical Systems 9 2 Coordination Issues in Self-organising Systems 13 2.1 Where all began: Linda ............................ 13 2.2 Leveraging Stochasticity . 14 2.2.1 SwarmLinda . 15 2.3 Leveraging Programmability . 16 2.3.1 ReSpecT ................................. 16 2.4 Putting all together . 18 2.4.1 Biochemical Tuple Spaces . 18 2.4.2 SAPERE . 19 2.5 Remarks & Outlook . 21 3 Re-thinking Stochastic, Programmable Coordination 23 3.1 Chemical Reactions as Coordination Laws . 23 3.1.1 Self-organisation Patterns . 24 3.1.2 Custom Kinetic Rates . 26 3.1.3 Discussion of Results . 43 3.2 Uniform Primitives as Coordination Primitives . 44 3.2.1 Related Approaches . 44 3.2.2 Informal Definition . 47 3.2.3 Informal Expressiveness . 50 3.2.4 Discussion of Results . 59 3.3 Formal Expressiveness of Uniform Primitives . 59 3.3.1 Formal Definition of Uniform Primitives . 60 3.3.2 From Modular Embedding to PME . 62 v 3.3.3 Relative Expressiveness Results . 69 3.3.4 Similar Approaches . 70 3.4 Remarks & Outlook . 71 4 Coordination Issues in Situated Pervasive Systems 73 4.1 The Quest toward Situatedness in MAS . 73 4.1.1 Review of Meta-models . 74 4.1.2 Review of Architectures . 78 4.1.3 A Reference Architecture . 83 4.2 Environmental Situatedness in TuCSoN .................... 87 4.2.1 Architectural Overview . 87 4.2.2 Flow of Interactions . 90 4.2.3 Implementation Methodology . 99 4.2.4 Discussion of Results . 107 4.2.5 Related Work . 107 4.3 Spatial Situatedness in TuCSoN ........................ 110 4.3.1 Space-aware Coordination Media . 111 4.3.2 Space-aware Extension to ReSpecT .................. 113 4.3.3 Expressiveness Showcase . 118 4.3.4 Discussion of Results . 122 4.4 Remarks & Outlook . 123 5 Coordination Issues in Knowledge-Intensive Socio-Technical Systems 125 5.1 Socio-Technical Systems & Knowledge-Intensive Environments . 125 5.1.1 Challenges of Socio-Technical Systems . 125 5.1.2 Challenges of Knowledge-Intensive Environments . 126 5.1.3 Research Roadmap . 128 5.2 From Activity Theory to Behavioural Implicit Communication . 129 5.2.1 Activity Theory for Multi-Agent Systems . 129 5.2.2 Stigmergy and Cognitive Stigmergy . 131 5.2.3 Behavioural Implicit Communication . 133 5.2.4 Toward Computational Smart Environments . 136 5.3 Behavioural Implicit Communication in Real-world STS . 138 5.3.1 Survey of Actions . 138 5.3.2 Factorisation of Common Actions . 143 5.4 Remarks & Outlook . 146 II Self-organisation of Knowledge in MoK 149 6 The M olecules of K nowledge Model 153 6.1 Core Abstractions . 154 vi 6.2 Focus on Reactions . 160 6.2.1 Formal Description . 160 6.2.2 Evaluation . 165 6.3 Focus on Interactions . 178 6.3.1 From Users' Actions to MoK Perturbations . 178 6.3.2 Early Evaluation: Citizen Journalism . 182 6.4 Focus on Similarity . 188 6.4.1 Viable Approaches . 189 6.4.2 Experiments . 191 7 The M olecules of K nowledge Technology 197 7.1 Prototype on TuCSoN ............................. 197 7.1.1 Main Abstractions . 198 7.1.2 The Chemical Engine Logic . 200 7.1.3 Spotlight on Engine Implementation . 204 7.1.4 Early Evaluation: MoK -News . 205 7.2 MoK Ecosystem . 214 7.2.1 Information Harvesting Layer . 216 7.2.2 Networking & Communication Layer . 217 III Conclusion & Outlook 223 8 Conclusion 225 9 Outlook 227 Bibliography 229 vii viii Chapter 1 About this Thesis Knowledge-Intensive Environments (KIE) are workplaces in which sustainability of the organisation long-term goals is influenced by, if not even dependant on, the evolution of the knowledge embodied within the organisation itself [Bha01]. Being knowledge an organised combination of data, procedures, and operations, continuously interacting and evolving according to human users practice and (learnt) experience, KIE are usually computationally supported by Socio-Technical Systems (STS), that is, systems in which cognitive and social interaction is mediated by information technology, rather than by the natural world alone [Whi06]. The modern IT landscape is increasingly pervaded by these kind of systems, mostly due to the astonishing amount of data available nowadays, and to the unprecedented participation of end users in the applications they use everyday|think about, e.g., social networks, crowdsourcing platforms, online collaboration tools, and the like. By definition, both KIE and STS are heavily interaction-centred, thus, they inevitably need to deal with coordination issues to harness the intricacies of run-time dependencies between the data and the agents (either software or human) participating the system [MC94]. However, engineering effective coordination is far from trivial, mostly due to a few peculiarities of KIE and STS: unpredictability of human behaviour, scalability of the technological infrastructure, size of the amount of data, information, and knowledge to handle, pace of knowledge production and consumption. For these reasons, this thesis approaches the issue of engineering knowledge-intensive STS from a coordination perspective, dealing with the aforementioned issues at the infras- tructural level. The goal is to enable and promote user-driven self-organisation of knowl- edge, by leveraging self-organising coordination mechanisms, an architecture for situated pervasive systems, and a cognitive model of social action. Accordingly, the contribution of this thesis may be conveniently articulated as follows: • Chapter 2 briefly reviews the literature about self-organising coordination • Chapter 3 describes the approach to coordination in self-organising systems, dealing 1 CHAPTER 1. ABOUT THIS THESIS with the well-known local vs. global issue by engineering coordination laws as artifi- cial chemical reactions. Simulations illustrate the potentiality of the approach, while a formal definition of the coordination primitives exploited as basic implementation bricks completes the analysis|along with a study of their expressiveness • Chapter 4 provides a distributed, situated architecture for coordination in perva- sive Multi-Agent Systems (MAS), supporting engineering of the aforementioned coordination laws, implemented by deeply extending and refactoring an existing coordination infrastructure. The coordination language exploited by the infrastruc- ture is accordingly extended so has to handle the novel abstractions, enabling and promoting situated coordination • Chapter 5 studies the Behavioural Implicit Communication (BIC) model of social action, bringing its abstractions and mechanisms into the (chemical-inspired, situ- ated) computational framework, so as to leverage the concept of tacit messages to enable user-driven coordination • Chapter 6 describes the M olecules of K nowledge model (MoK ) for self-organisation of knowledge in knowledge-intensive STS • Chapter 7 discusses the MoK technology, describing both a prototype middleware and a complete eco-system currently under development Chapters are further arranged in two parts: Part I includes chapters 2 to 5, Part II chapters 6 and 7.