Coordination of Complex Sociotechnical Systems. Self-Organisation of Knowledge in MoK (uncorrected proof)

233 Pages·2016·7.082 MB·english

by  Stefano Mariani

Stefano Mariani
Coordination of Complex
Sociotechnical Systems
MoK
Self-organisation of Knowledge in
123
16 StefanoMariani
17 Dipartimento di Informatica - Scienzae
18 Ingegneria(DISI)
19 Universitàdi Bologna
20 Bologna
21 Italy
2267 ISSN 2365-3051 ISSN 2365-306X (electronic)
28 ArtificialIntelligence: Foundations, Theory,andAlgorithms
2390 ISBN978-3-319-47108-2 ISBN978-3-319-47109-9 (eBook)
31 DOI 10.1007/978-3-319-47109-9
32
33 LibraryofCongressControlNumber:2016954906
34
35 ©SpringerInternationalPublishingAG2016
49
50 ThisSpringerimprintispublishedbySpringerNature
51 TheregisteredcompanyisSpringerInternationalPublishingAG
52 Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland
Foreword
60 Modern societies are organised around a number of (interdependent) complex
61 systems. Logistic and supply chains, transportation networks, health services,
62 energy systems, financial markets, and smart cities are just a few examples. These
63 systems are inherently sociotechnical and involve interactions between infrastruc-
64 tures, man-made processes, natural phenomena, multiple stakeholders, and human
65 behaviour. Also, their dynamic arises from interaction of a population of
66 self-interested agents, coordinating/competing locally with one another as well as
67 with their environment.Normally there is no centralised control structure dictating
68 how individuals should behave, and local agent-to-agent interaction often leads to
69 the emergence of global self-organised behaviour.
70 For instance, in road network infrastructures with traffic light controllers,
71 road-sideunits,and a communication networkbetween intersections (the technical
72 part), drivers (the human/social component of the system) are self-interested
73 autonomous entities that cannot be directly controlled by a central planner, but
74 rather take decisions according to their own utility function—for instance, min-
75 imisation of their travel-time. In traffic networks, queues and congestions arise as
76 system emergent behaviours. In order to avoid them, no centralised control can be
77 exploited: instead, single suggestions based on traffic data harvested by either
78 sensorsorroad-sideunitscouldbeprovidedtodrivers,whointurnmightchooseto
79 change their current plans.
80 Sociotechnicalsystemsareheavilyknowledge-intensive.Forthefirsttimeinthe
81 history of mankind, we have access to data sets of unprecedented scale and accu-
82 racy about infrastructures, processes, natural phenomena, and human behaviours.
83 Global systems rely on the Internet of Things, where each object is connected and
84 generatesdata.Extractingusefulknowledgefromsuchanenormousamountofdata
85 is essential to design effective control strategies, as well as to construct efficient
86 strategic and tactical planning tools.
87 In the last 5 years, my research has been focussed on the design and imple-
88 mentation of decision support tools deciding on such complex systems. While
89 traditional modelling techniques have always relied on domain expert knowledge,
90 thecomplexityofsociotechnicalsystemscallsforanewmodellingparadigmwhere
91 a relevant part of the model is learned from data harvested by sensors, producing
92 observations from heterogeneous data sources. Organising data, clustering them
93 according to their relevance for a specific topic, and extracting modelling compo-
94 nents from them constitute a cornerstone of empirical model learning.
95 This book, written by a young and extremely talented researcher, is about
96 studying and engineering coordination mechanisms in knowledge-intensive
97 sociotechnical systems that are heavily affected by the scale, unpredictability,
98 non-determinism,andamountandpaceofdatatheyrelyon.Alltheabovefeatures
99 imply challenges that can be approached via a paradigm shift in the coordination
100 perspective: accordingly, the book defines new techniques supporting pro-
101 grammable, self-organising, situated coordination.
102 The main idea behind self-organising coordination takes inspiration from the
103 socio-cognitivetheoryofaction,andproposesanintriguingconceptofMolecules
104 of Knowledge(MoK).TheMoK modelisbuiltaroundabiochemicalmetaphor
105 where information sources are continuously and spontaneously enriched via
106 information chunks that autonomously aggregate on the basis of user interaction,
107 and gain or lose relevance as time flows. This way, data may become organised
108 information autonomously, guided by coordination mechanisms seamlessly inte-
109 grating knowledge. In addition, data behave as continuously alive entities, by
110 re-organisingthemselvesspontaneously,andbyevolvingthemselvestobettermeet
111 the ever-changing needs of the system they describe.
112 TheMoK metaphorhasapotentiallytremendousimpactonanumberoffields:
113 from information gathering in the Internet to distributed control strategies relying
114 on heterogeneous data sources; from predictive systems extracting models from
115 observation to prescriptive systems where data and observation are essential to
116 characterise the system and learn model components.
MoK
117 Also, by adopting an engineering perspective, the metaphor poses a
118 number of interesting and far from trivial challenges. Along with the model, the
119 book proposes a well-detailed middleware layer for knowledge management
MoK
120 applications.Theoriginalimplementationofthe middlewareisbuiltuponthe
121 TuCSoN coordination infrastructure for distribution issues, and the ReSpecT
122 languageforspatio-temporalawarenessandadaptiveness.Themiddlewaresupports
123 programmable coordination for dealing with unpredictable and adaptive behaviour
124 and uncertain data, enables the emergence of self-organisation, and supports both
125 mutual and peripheral awareness thanks to situatedness.
126 I have known Stefano Mariani during his Ph.D. thesis, as I was at the internal
127 reviewing committee. I have been immediately impressed by the intriguing ideas
128 proposedinhisresearchactivity,bythedeeptechnologicalfoundationstheyrelied
129 on, and by the forward-looking vision of his Ph.D. work.
130 Stefano Mariani’s book is an excellent contribution to the field of knowledge
131 managementinenvironmentswherenon-determinism,unpredictability,uncertainty,
132 and complexity make traditional coordination mechanisms no longer usable. It
133 proposes an exciting model, covers engineering aspects, and attempts to discern
134 future directions ina fast-moving andinnovative field.
135 Bologna, Italy Michela Milano
136 July 2016
Preface
139 This book stems from the author’s own Ph.D. thesis, with the goal of providing a
140 coherent and comprehensive view over a paradigm shift in computational infor-
141 mationmanagementsystems,goingtowardself-organisationofinformationpieces,
142 interpreted as living entities spontaneously adapting to users’ needs according to
143 their behaviour. The purpose is to provide graduate students, junior and senior
144 researchers,information systemsdesigners, andknowledge practitioners ingeneral
145 with a novel perspective over knowledge and information management, supported
146 bypractical referenceguidelines,models, mechanisms,andtechnologies toexploit
147 during design of their system.
148 Thebookisthusstructuredtogracefullyintroducethereadertothecoordination
149 perspectiveovercomplexsociotechnicalsystems,bydiscussingafewexamplesof
150 such a sort of systems, namely distributed first, self-organising then, finally per-
151 vasive ones. Once the reader is more familiar with the aforementioned approaches
152 to coordination, she is presented a comprehensive model for self-organising coor-
153 dination of knowledge-intensive sociotechnical systems, which is thoroughly
154 described and discussed in both theoretical and technological aspects.
155 Theresearchlandscapethatthecontentsofthisbookconceptuallybelongtoisat
156 the crossroads between multi-agent systems, nature-inspired self-organisation, sit-
157 uated coordination, and sociotechnical systems. Accordingly, the more technical
158 contentstakeasareferenceagent-orientedmodels,consideringalsohumanagents,
159 where coordination occurs through environmentmediation, thus ina setting where
160 agents’actionsarealways situated inavirtual orphysical environment,andwhere
161 such an environment is able to spontaneously enact computational processes sup-
162 porting and promoting self-organisation of the agents ensemble.
163 Cesena, Italy Stefano Mariani
164 June 2016
Contents
119978 1 Introduction... .... .... ..... .... .... .... .... .... ..... .... 1
129090 1.1 Introduction .. .... ..... .... .... .... .... .... ..... .... 1
220012 1.2 Organisation of Chapters . .... .... .... .... .... ..... .... 3
220034 1.2.1 Part I. .... ..... .... .... .... .... .... ..... .... 3
220056 1.2.2 Part II .... ..... .... .... .... .... .... ..... .... 4
220078 1.2.3 Part III.... ..... .... .... .... .... .... ..... .... 5
220190 References. .... .... .... ..... .... .... .... .... .... ..... .... 5
221112 Part I Coordination of Complex Sociotechnical Systems
221134 2 Coordination of Distributed Systems.... .... .... .... ..... .... 9
221156 2.1 Tuple-Based Coordination .... .... .... .... .... ..... .... 9
221178 2.1.1 On Distribution.. .... .... .... .... .... ..... .... 10
221290 2.2 Programmable Coordination... .... .... .... .... ..... .... 12
222212 2.2.1 LGI.. .... ..... .... .... .... .... .... ..... .... 12
222234 2.2.2 GAMMA ... ..... .... .... .... .... .... ..... .... 14
222256 2.2.3 Tuple Centres and ReSpecT ... .... .... ..... .... 15
222278 2.2.4 TOTA .... ..... .... .... .... .... .... ..... .... 16
222390 2.3 Probabilistic Coordination. .... .... .... .... .... ..... .... 19
223312 2.3.1 pKLAIM ... ..... .... .... .... .... .... ..... .... 19
223334 2.3.2 SwarmLinda .... .... .... .... .... .... ..... .... 20
223356 References. .... .... .... ..... .... .... .... .... .... ..... .... 21
223378 3 Coordination of Self-organising Systems. .... .... .... ..... .... 25
223490 3.1 Bio-Inspired Self-organisation Patterns... .... .... ..... .... 25
224412 3.1.1 Spreading . ..... .... .... .... .... .... ..... .... 26
224434 3.1.2 Aggregation..... .... .... .... .... .... ..... .... 27
224456 3.1.3 Evaporation..... .... .... .... .... .... ..... .... 27
224478 3.1.4 Repulsion . ..... .... .... .... .... .... ..... .... 28
224590 3.1.5 Other Patterns ... .... .... .... .... .... ..... .... 28
225512 3.2 Nature-Inspired Coordination .. .... .... .... .... ..... .... 29
225534 3.2.1 Biochemical Tuple Spaces.. .... .... .... ..... .... 30
225556 3.2.2 SAPERE.. ..... .... .... .... .... .... ..... .... 31
225578 3.3 Chemical Reactions as Coordination Laws.... .... ..... .... 33
225690 3.3.1 Selected Patterns Encoding . .... .... .... ..... .... 34
226612 3.3.2 Custom Kinetic Rates . .... .... .... .... ..... .... 35
226634 3.4 Uniform Primitives as Coordination Primitives. .... ..... .... 52
226656 3.4.1 Related Approaches... .... .... .... .... ..... .... 53
226678 3.4.2 Informal Definition ... .... .... .... .... ..... .... 56
226790 3.4.3 Informal Expressiveness ... .... .... .... ..... .... 59
227712 3.4.4 Formalisation.... .... .... .... .... .... ..... .... 69
227734 References. .... .... .... ..... .... .... .... .... .... ..... .... 72
227756 4 Coordination of Pervasive Systems . .... .... .... .... ..... .... 77
227778 4.1 The Quest Towards Situatedness in MAS. .... .... ..... .... 77
227890 4.1.1 Review of Meta-Models ... .... .... .... ..... .... 78
228812 4.1.2 Review of Architectures ... .... .... .... ..... .... 82
228834 4.1.3 A Reference Architecture .. .... .... .... ..... .... 87
228856 4.2 On Situated Coordination. .... .... .... .... .... ..... .... 90
228878 4.3 Environmental Situatedness in TuCSoN . .... .... ..... .... 91
228990 4.3.1 Architectural Overview .... .... .... .... ..... .... 91
229912 4.3.2 Flow of Interactions... .... .... .... .... ..... .... 95
229934 4.3.3 Methodology: Example Scenario. .... .... ..... .... 101
229956 4.3.4 Related Work ... .... .... .... .... .... ..... .... 103
229978 4.4 Temporal Situatedness in ReSpecT. .... .... .... ..... .... 105
239090 4.4.1 Time-Aware Coordination Media .... .... ..... .... 105
330012 4.4.2 Time-Aware Extension to ReSpecT.. .... ..... .... 107
330034 4.4.3 Expressiveness Showcase .. .... .... .... ..... .... 108
330056 4.5 Spatial Situatedness in ReSpecT... .... .... .... ..... .... 112
330078 4.5.1 Space-Aware Coordination Media.... .... ..... .... 112
330190 4.5.2 Space-Aware Extension to ReSpecT . .... ..... .... 115
331112 4.5.3 Expressiveness Showcase .. .... .... .... ..... .... 119
331134 References. .... .... .... ..... .... .... .... .... .... ..... .... 124
331156 5 Coordination of Sociotechnical Systems.. .... .... .... ..... .... 129
317 5.1 Sociotechnical Systems and Knowledge-Intensive
331189 Environments . .... ..... .... .... .... .... .... ..... .... 129
332201 5.1.1 Challenges of Sociotechnical Systems. .... ..... .... 129
332223 5.1.2 Challenges of Knowledge-Intensive Environments .... 131
332245 5.1.3 Research Roadmap ... .... .... .... .... ..... .... 132
326 5.2 From Activity Theory to Behavioural Implicit
332278 Communication.... ..... .... .... .... .... .... ..... .... 133
332390 5.2.1 Activity Theory for Multi-agent Systems... ..... .... 134
333312 5.2.2 The A&A Meta-Model .... .... .... .... ..... .... 134
333334 5.2.3 Stigmergy and Cognitive Stigmergy .. .... ..... .... 136
333356 5.2.4 Behavioural Implicit Communication . .... ..... .... 138
333378 5.2.5 Toward Computational Smart Environments..... .... 141
333490 5.3 Behavioural Implicit Communication in Real-World STS.. .... 143
334412 5.3.1 Survey of Actions.... .... .... .... .... ..... .... 143
334434 5.3.2 Factorisation of Common Actions.... .... ..... .... 147
334456 References. .... .... .... ..... .... .... .... .... .... ..... .... 151
M o K
334478 Part II Self-organisation of Knowledge in olecules f nowledge
M o K
334590 6 olecules f nowledge: Model ... .... .... .... .... ..... .... 155
335512 6.1 Motivation, Context, Goal .... .... .... .... .... ..... .... 155
335534 6.2 Core Abstractions.. ..... .... .... .... .... .... ..... .... 157
335556 6.2.1 Atoms .... ..... .... .... .... .... .... ..... .... 157
335578 6.2.2 Seeds. .... ..... .... .... .... .... .... ..... .... 158
335690 6.2.3 Molecules . ..... .... .... .... .... .... ..... .... 159
336612 6.2.4 Catalysts .. ..... .... .... .... .... .... ..... .... 160
336634 6.2.5 Enzymes .. ..... .... .... .... .... .... ..... .... 160
336656 6.2.6 Traces .... ..... .... .... .... .... .... ..... .... 161
336678 6.2.7 Perturbations .... .... .... .... .... .... ..... .... 162
336790 6.2.8 Reactions.. ..... .... .... .... .... .... ..... .... 163
337712 6.2.9 Compartments... .... .... .... .... .... ..... .... 164
337734 6.2.10 Membranes ..... .... .... .... .... .... ..... .... 164
337756 6.3 Computational Model: Artificial Chemical Reactions..... .... 165
337778 6.3.1 Injection .. ..... .... .... .... .... .... ..... .... 165
337890 6.3.2 Aggregation..... .... .... .... .... .... ..... .... 166
338812 6.3.3 Diffusion.. ..... .... .... .... .... .... ..... .... 167
338834 6.3.4 Decay .... ..... .... .... .... .... .... ..... .... 168
338856 6.3.5 Reinforcement... .... .... .... .... .... ..... .... 169
338878 6.3.6 Deposit ... ..... .... .... .... .... .... ..... .... 170
338990 6.3.7 Perturbation..... .... .... .... .... .... ..... .... 170
391 6.4 Interaction Model: Epistemic Actions, Tacit Messages,
339923 and Perturbation Actions.. .... .... .... .... .... ..... .... 171
339945 6.4.1 Share. .... ..... .... .... .... .... .... ..... .... 172
339967 6.4.2 Mark. .... ..... .... .... .... .... .... ..... .... 173
339989 6.4.3 Annotate .. ..... .... .... .... .... .... ..... .... 174
440001 6.4.4 Connect... ..... .... .... .... .... .... ..... .... 174
440023 6.4.5 Harvest ... ..... .... .... .... .... .... ..... .... 175
404 6.5 Information Model: Representation and Similarity-Based
440056 Matchmaking . .... ..... .... .... .... .... .... ..... .... 176
440078 References. .... .... .... ..... .... .... .... .... .... ..... .... 178
M o K
440190 7 olecules f nowledge: Technology... .... .... .... ..... .... 181
441112 7.1 Prototype on TuCSoN... .... .... .... .... .... ..... .... 181
441134 7.1.1 Core Abstractions Mapping. .... .... .... ..... .... 182
441156 7.1.2 The Chemical Engine Logic .... .... .... ..... .... 184
441178 7.1.3 Spotlight on Engine Implementation.. .... ..... .... 187
441290 7.2 Software Ecosystem ..... .... .... .... .... .... ..... .... 189
442212 7.2.1 Information Harvesting Layer ... .... .... ..... .... 191
442234 7.2.2 Networking and Communication Layer.... ..... .... 192
442256 7.2.3 User Interaction Layer. .... .... .... .... ..... .... 196
442278 References. .... .... .... ..... .... .... .... .... .... ..... .... 197
M o K
442390 8 olecules f nowledge: Simulation ... .... .... .... ..... .... 199
443312 8.1 Computational Model.... .... .... .... .... .... ..... .... 199
443334 8.1.1 Injection .. ..... .... .... .... .... .... ..... .... 201
443356 8.1.2 Decay .... ..... .... .... .... .... .... ..... .... 202
443378 8.1.3 Aggregation..... .... .... .... .... .... ..... .... 204
443490 8.1.4 Reinforcement... .... .... .... .... .... ..... .... 206
444412 8.1.5 Diffusion.. ..... .... .... .... .... .... ..... .... 208
444434 8.2 Interaction Model.. ..... .... .... .... .... .... ..... .... 210
444456 References. .... .... .... ..... .... .... .... .... .... ..... .... 215
M o K
444478 9 olecules f nowledge: Case Studies.. .... .... .... ..... .... 217
444590 9.1 Similarity-Based Clustering ... .... .... .... .... ..... .... 217
445512 9.1.1 Basic Measure... .... .... .... .... .... ..... .... 218
445534 9.1.2 Cosine Similarity. .... .... .... .... .... ..... .... 219
445556 9.1.3 Concept-Based Similarity .. .... .... .... ..... .... 220
445578 9.2 MoK-News... .... ..... .... .... .... .... .... ..... .... 222
445690 9.2.1 Knowledge Representation for News Management .... 222
MoK
446612 9.2.2 Incarnation of Model. .... .... .... ..... .... 224
446634 9.2.3 MoK-News at Work . .... .... .... .... ..... .... 225
446656 References. .... .... .... ..... .... .... .... .... .... ..... .... 228
446678 Part III Conclusion
446790 10 Conclusion.... .... .... ..... .... .... .... .... .... ..... .... 233
447712 10.1 Conclusive Remarks..... .... .... .... .... .... ..... .... 233