Parallel Relational Universes – experiments in modularity

We here describe Parallel Relational Universes, an artistic method used for the psychological analysis of group dynamics. The design of the artistic system, which mediates group dynamics, emerges from our studies of modular playware and remixing playware. Inspired from remixing modular playware, where users remix samples in the form of physical and functional modules, we created an artistic instantiation of such a concept with the Parallel Relational Universes, allowing arts alumni to remix artistic expressions. Here, we report the data emerged from a first pre-test, run with gymnasium’s alumni. We then report both the artistic and the psychological findings. We discuss possible variations of such an instrument. Between an art piece and a psychological test, at a first cognitive analysis, it seems to be a promising research tool

The Mental Database

This article uses database, evolution and physics considerations to suggest how the mind stores and processes its data. Its innovations in its approach lie in:- A) The comparison between the capabilities of the mind to those of a modern relational database while conserving phenomenality. The strong functional similarity of the two systems leads to the conclusion that the mind may be profitably described as being a mental database. The need for material/mental bridging and addressing indexes is discussed. B) The consideration of what neural correlates of consciousness (NCC) between sensorimotor data and instrumented observation one can hope to obtain using current biophysics. It is deduced that what is seen using the various brain scanning methods reflects only that part of current activity transactions (e.g. visualizing) which update and interrogate the mind, but not the contents of the integrated mental database which constitutes the mind itself. This approach yields reasons why there is much neural activity in an area to which a conscious function is ascribed (e.g. the amygdala is associated with fear), yet there is no visible part of its activity which can be clearly identified as phenomenal. The concept is then situated in a Penrosian expanded physical environment, requiring evolutionary continuity, modularity and phenomenality.Several novel Darwinian advantages arising from the approach are described

Non-human actors in their "strongly possible worlds" : constructions of alternative universes in Bio Art Projects

The article is an introduction that examines certain perspectives of new-materialist research on the ontological status of alternative universes in bio art projects with reference to the narratological concepts of possible worlds and the storyworld. In this context, it introduces the concept of "strongly possible worlds", which is a complementary concept to the Jan Alber's theory of impossible worlds. This methodological proposal is also presented in the article in reference to the latest study by Francesca Ferrando, in which the idea of "posthuman multiverse" was presented. The author also considers the role of non-human actors in the process of constructing such "in the world stories" (Bruno Latour). As non-human actors bacteria and living cells are understood, which have their own intentionality (goal-oriented behavior) and which are responsible for causal changes to the project; moreover, non-human actors are considered to be a force that aff ects the physical shape of storyworlds - with reference to Timothy Morton's category of hyperobjects. The article presents two types of experiments involving the process of creation of possible worlds in bio art. The fi rst one is conducted by the artists working with living materials, mostly tissues and cells, as the duo Tissue Culture and Art Project, Alicia King and Guy Ben-Ary and Kirsten Hudson; the other one is so called bacterial art with Sonja Bäumel's "Expanded body", Pinar Yoldas "Speculative biologies" and "Ecosystem of Excess", as well as Anna Dumitriu's artistic vision "The Romantic Disease: An Artistic Investigation of Tuberculosis" and "ArchaeaBot: A Post Climate Change, Post Singularity Life-form" as special case studies

Dagstuhl News January - December 2007

"Dagstuhl News" is a publication edited especially for the members of the Foundation "Informatikzentrum Schloss Dagstuhl" to thank them for their support. The News give a summary of the scientific work being done in Dagstuhl. Each Dagstuhl Seminar is presented by a small abstract describing the contents and scientific highlights of the seminar as well as the perspectives or challenges of the research topic

Digital Well-Being as a New Kind of Adaptation to the New Millennium Needs: A State-of-the-Art Analysis

AbstractSince technology has been entering into human beings’ everyday life, individuals established a deep relationship with digital technology, thus an embodied link between people and digital instruments has been born. This is particularly evidenced by recent literature about screen time (duration of time spent by the individual in using electronic/digital media like television, smartphone, tablet or computer), it significantly influences different human beings’ dimensions: physical, psychological and neurological functions. Impact of digital technology on human beings can be considered as a result of syntonic functioning in order to improve different people’s life areas (e.g., work, social or intimate relationship, learning), while the dystonic relationship is evidenced as a result of human addiction to digital technology. The present study aims to provide a cognitive and social psychology perspective on how screen time is changing our existences, defining digital technology as a gift which people should be aware of in terms of positive but even negative consequences in everyday life

On the Synthesis of fuzzy neural systems.

by Chung, Fu Lai.Thesis (Ph.D.)--Chinese University of Hong Kong, 1995.Includes bibliographical references (leaves 166-174).ACKNOWLEDGEMENT --- p.iiiABSTRACT --- p.ivChapter 1. --- Introduction --- p.1Chapter 1.1 --- Integration of Fuzzy Systems and Neural Networks --- p.1Chapter 1.2 --- Objectives of the Research --- p.7Chapter 1.2.1 --- Fuzzification of Competitive Learning Algorithms --- p.7Chapter 1.2.2 --- Capacity Analysis of FAM and FRNS Models --- p.8Chapter 1.2.3 --- Structure and Parameter Identifications of FRNS --- p.9Chapter 1.3 --- Outline of the Thesis --- p.9Chapter 2. --- A Fuzzy System Primer --- p.11Chapter 2.1 --- Basic Concepts of Fuzzy Sets --- p.11Chapter 2.2 --- Fuzzy Set-Theoretic Operators --- p.15Chapter 2.3 --- "Linguistic Variable, Fuzzy Rule and Fuzzy Inference" --- p.19Chapter 2.4 --- Basic Structure of a Fuzzy System --- p.22Chapter 2.4.1 --- Fuzzifier --- p.22Chapter 2.4.2 --- Fuzzy Knowledge Base --- p.23Chapter 2.4.3 --- Fuzzy Inference Engine --- p.24Chapter 2.4.4 --- Defuzzifier --- p.28Chapter 2.5 --- Concluding Remarks --- p.29Chapter 3. --- Categories of Fuzzy Neural Systems --- p.30Chapter 3.1 --- Introduction --- p.30Chapter 3.2 --- Fuzzification of Neural Networks --- p.31Chapter 3.2.1 --- Fuzzy Membership Driven Models --- p.32Chapter 3.2.2 --- Fuzzy Operator Driven Models --- p.34Chapter 3.2.3 --- Fuzzy Arithmetic Driven Models --- p.35Chapter 3.3 --- Layered Network Implementation of Fuzzy Systems --- p.36Chapter 3.3.1 --- Mamdani's Fuzzy Systems --- p.36Chapter 3.3.2 --- Takagi and Sugeno's Fuzzy Systems --- p.37Chapter 3.3.3 --- Fuzzy Relation Based Fuzzy Systems --- p.38Chapter 3.4 --- Concluding Remarks --- p.40Chapter 4. --- Fuzzification of Competitive Learning Networks --- p.42Chapter 4.1 --- Introduction --- p.42Chapter 4.2 --- Crisp Competitive Learning --- p.44Chapter 4.2.1 --- Unsupervised Competitive Learning Algorithm --- p.46Chapter 4.2.2 --- Learning Vector Quantization Algorithm --- p.48Chapter 4.2.3 --- Frequency Sensitive Competitive Learning Algorithm --- p.50Chapter 4.3 --- Fuzzy Competitive Learning --- p.50Chapter 4.3.1 --- Unsupervised Fuzzy Competitive Learning Algorithm --- p.53Chapter 4.3.2 --- Fuzzy Learning Vector Quantization Algorithm --- p.54Chapter 4.3.3 --- Fuzzy Frequency Sensitive Competitive Learning Algorithm --- p.58Chapter 4.4 --- Stability of Fuzzy Competitive Learning --- p.58Chapter 4.5 --- Controlling the Fuzziness of Fuzzy Competitive Learning --- p.60Chapter 4.6 --- Interpretations of Fuzzy Competitive Learning Networks --- p.61Chapter 4.7 --- Simulation Results --- p.64Chapter 4.7.1 --- Performance of Fuzzy Competitive Learning Algorithms --- p.64Chapter 4.7.2 --- Performance of Monotonically Decreasing Fuzziness Control Scheme --- p.74Chapter 4.7.3 --- Interpretation of Trained Networks --- p.76Chapter 4.8 --- Concluding Remarks --- p.80Chapter 5. --- Capacity Analysis of Fuzzy Associative Memories --- p.82Chapter 5.1 --- Introduction --- p.82Chapter 5.2 --- Fuzzy Associative Memories (FAMs) --- p.83Chapter 5.3 --- Storing Multiple Rules in FAMs --- p.87Chapter 5.4 --- A High Capacity Encoding Scheme for FAMs --- p.90Chapter 5.5 --- Memory Capacity --- p.91Chapter 5.6 --- Rule Modification --- p.93Chapter 5.7 --- Inference Performance --- p.99Chapter 5.8 --- Concluding Remarks --- p.104Chapter 6. --- Capacity Analysis of Fuzzy Relational Neural Systems --- p.105Chapter 6.1 --- Introduction --- p.105Chapter 6.2 --- Fuzzy Relational Equations and Fuzzy Relational Neural Systems --- p.107Chapter 6.3 --- Solving a System of Fuzzy Relational Equations --- p.109Chapter 6.4 --- New Solvable Conditions --- p.112Chapter 6.4.1 --- Max-t Fuzzy Relational Equations --- p.112Chapter 6.4.2 --- Min-s Fuzzy Relational Equations --- p.117Chapter 6.5 --- Approximate Resolution --- p.119Chapter 6.6 --- System Capacity --- p.123Chapter 6.7 --- Inference Performance --- p.125Chapter 6.8 --- Concluding Remarks --- p.127Chapter 7. --- Structure and Parameter Identifications of Fuzzy Relational Neural Systems --- p.129Chapter 7.1 --- Introduction --- p.129Chapter 7.2 --- Modelling Nonlinear Dynamic Systems by Fuzzy Relational Equations --- p.131Chapter 7.3 --- A General FRNS Identification Algorithm --- p.138Chapter 7.4 --- An Evolutionary Computation Approach to Structure and Parameter Identifications --- p.139Chapter 7.4.1 --- Guided Evolutionary Simulated Annealing --- p.140Chapter 7.4.2 --- An Evolutionary Identification (EVIDENT) Algorithm --- p.143Chapter 7.5 --- Simulation Results --- p.146Chapter 7.6 --- Concluding Remarks --- p.158Chapter 8. --- Conclusions --- p.159Chapter 8.1 --- Summary of Contributions --- p.160Chapter 8.1.1 --- Fuzzy Competitive Learning --- p.160Chapter 8.1.2 --- Capacity Analysis of FAM and FRNS --- p.160Chapter 8.1.3 --- Numerical Identification of FRNS --- p.161Chapter 8.2 --- Further Investigations --- p.162Appendix A Publication List of the Candidate --- p.164BIBLIOGRAPHY --- p.16

Statistical physics approaches to large-scale socio-economic networks

Die statistische Physik erforschte im letzten Jahrzehnt eine Fülle von wissenschaftlichen Gebieten, was zu einem besseren quantitativen Verständnis von verschiedenen, aus vielen Elementen bestehenden Systemen, z.B. von sozialen Systemen, geführt hat. Eine empirische Quantifizierung von menschlichem Verhalten auf gesellschaftlichem Niveau hat sich allerdings bisher als sehr schwierig erwiesen, wegen Problemen bei der Gewinnung und Qualität von Daten. In dieser Doktorarbeit erstellen wir zum ersten mal einen umfangreichen über fünf Jahre gesammelten Datensatz, der praktisch alle Aktionen und Eigenschaften der 350.000 Teilnehmer einer gesamten menschlichen Gesellschaft aus einem selbstentwickelten Massive Multiplayer Online Game enthält. Wir beschreiben dieses aus stark wechselwirkenden Spielern bestehende soziale System in drei Ebenen. In einem ersten Schritt analysieren wir die Individuen und deren Verhalten im Verlauf der Zeit. Eine Skalen- und Fluktuationsanalyse von Aktions-Reaktions-Zeitreihen enthüllt Persistenz der möglichen Aktionen und qualitative Unterschiede zwischen "guten" und "schlechten" Spielern. Wir untersuchen danach den Diffusionsprozess der im Spieluniversum stattfindenden Bewegungen der Individuen. Wir finden Subdiffusivität und eine durch ein Potenzgesetz verteilte Präferenz zu kürzlich besuchten Orten zurückzukehren. Zweitens, auf der nächsthöheren Ebene, verwenden wir Netzwerktheorie um die topologische Struktur der Interaktionen zwischen Individuen zu quantifizieren. Wir konzentrieren uns auf sechs durch direkte Interaktionen definierte Netzwerke, drei davon positiv (Handel, Freundschaft, Kommunikation), drei negativ (Feindschaft, Attacke, Bestrafung). Diese Netzwerke weisen nichttriviale statistische Eigenschaften auf, z.B. skaleninvariante Topologie, und entwickeln sich in der Zeit, was uns erlaubt eine Reihe von Hypothesen über sozialdynamische Phänomene zu testen. Wir finden qualitative Unterschiede zwischen positiven und negativen Netzwerken in Evolution und Struktur. Schließlich untersuchen wir das Multiplex-Netzwerk der Spielergesellschaft, das sich aus den einzelnen Netzwerk-Schichten zusammensetzt. Wir quantifizieren Interaktionen zwischen verschiedenen Netzwerken und zeigen die nichttrivialen Organisationsprinzipien auf die auch in echten menschlichen Gesellschaften beobachtet wurden. Unsere Erkenntnisse liefern Belege für die Hypothese der strukturellen Balance, die eine Vermeidung von gewissen frustrierten Zuständen auf mikroskopischem Niveau postuliert. Mit diesem Aufbau demonstrieren wir die Möglichkeit der Gewinnung neuartiger wissenschaftlicher Erkenntnisse über die Natur von kollektivem menschlichen Verhalten in großangelegten sozialen Systemen.In the past decade a variety of fields has been explored by statistical physicists, leading to an increase of our quantitative understanding of various systems composed of many interacting elements, such as social systems. However, an empirical quantification of human behavior on a societal level has so far proved to be tremendously difficult due to problems in data availability, quality and ways of acquisition. In this doctoral thesis we compile for the first time a large-scale data set consisting of practically all actions and properties of 350,000 odd participants of an entire human society interacting in a self-developed Massive Multiplayer Online Game, over a period of five years. We describe this social system composed of strongly interacting players in the game in three consecutive levels. In a first step, we examine the individuals and their behavioral properties over time. A scaling and fluctuation analysis of action-reaction time-series reveals persistence of the possible actions and qualitative differences between "good" and "bad" players. We then study and model the diffusion process of human mobility occurring within the "game universe". We find subdiffusion and a power-law distributed preference to return to more recently visited locations. Second, on a higher level, we use network theory to quantify the topological structure of interactions between the individuals. We focus on six network types defined by direct interactions, three of them with a positive connotation (trade, friendship, communication), three with a negative one (enmity, attack, punishment). These networks exhibit non-trivial statistical properties, e.g. scale-free topology, and evolve over time, allowing to test a series of long-standing social-dynamics hypotheses. We find qualitative differences in evolution and topological structure between positive and negative tie networks. Finally, on a yet higher level, we consider the multiplex network of the player society, constituted by the coupling of the single network layers. We quantify interactions between different networks and detect the non-trivial organizational principles which lead to the observed structure of the system and which have been observed in real human societies as well. Our findings with the multiplex framework provide evidence for the half-century old hypothesis of structural balance, where certain frustrated states on a microscopic level tend to be avoided. Within this setup we demonstrate the feasibility for generating novel scientific insights on the nature of collective human behavior in large-scale social systems

Hacking the museum? Collections makerspaces and power in London cultural institutions

What happens when the spaces of grassroots digital subcultures encounter those of institutions? This thesis examines the phenomenon of ‘collections makerspaces’, or public spaces within cultural institutions that encourage experimental interactions with cultural artefacts through digitally-mediated making and learning practices. I begin by working from a genealogical approach to locate collections makerspaces as parts of a wider historical lineage of sociotechnical transformations amongst makerspaces (from hackspaces to media labs) and cultural institutions in the U.K. from the 1970s onward, relations increasingly characterised by institutional partnerships. I engage with a critical theoretical framework of space and power to explore how the spatiality of collections makerspaces is constituted out of the practices, imaginaries and relations of multiple actors. This enables me to situate space-making as a process, which may reinforce or resist institutional logics. I then explore the empirical findings of my fieldwork as researcher-in-residence at four collections makerspaces in London at Tate Britain, Tate Modern, the British Museum and the Wellcome Collection. Working with a qualitative ethnographic and action research methodology, I draw from 255 hours of participant observation, 67 chats with site users, expert interviews with 38 facilitators, and 4 creative interventions to explore the circumstances of each field site, the experiences of those who are involved in it, and how it interacts with its host institution. I conclude by arguing that collections makerspaces provide significant value to cultural institutions and publics alike, because they facilitate new opportunities for the cultural hegemony of museum logics to be examined, contested and transformed through material participation. I propose the spatial frame of ‘decoupaged space’ as a lens to explore the informal cultural production of other kinds of co-creational digital spaces within institutions. This allows me to assert the broader social impacts of sites of this kind, by articulating the powergeometries of agency, access, diversity and mobility that they can reframe

Mind, meaning and miscommunication

I examine various instances of miscommunication to look for factors that might provide a clearer understanding of the nature of meaning. My focus is on how meaning relates to mind. I am therefore concerned primarily with utterances as linguistic units in themselves, and only secondarily with propositions and speech acts formed from utterances. I approach the task on the basis of the modularity of mind, and consider cases of miscommunication under three headings: (a) the acquisition of meaning (how children acquire language and thereby meaning); (b) the expression of meaning (factors that determine how we express meaning in our utterances); and (c) the extraction of meaning (how we determine the meaning of utterances). I review various philosophical approached to meaning, including those of Davidson, Frege, Grice, Putnam, Searle and Tarski. I assess their strengths and weaknesses in the light of the cases of miscommunication that have some bearing upon them. In the final part of the thesis I attempt to provide a coherent account of what meaning is, and how meaning and language are related, before suggesting in conclusion that my proposed account of meaning fits well with the modular theory of mind

Data Model Verification via Theorem Proving

Software applications have moved from desktop computers onto the web. This is not surprising since there are many advantages that web applications provide, such as ubiquitous access and distributed processing power. However, these benefits come at a cost. Web applications are complex distributed systems written in multiple languages. As such, they are prone to errors at any stage of development, and difficult to verify, or even test. Considering that web applications store and manage data for millions (even billions) of users, errors in web applications can have disastrous effects.In this dissertation, we present a method for verifying code that is used to access and modify data in web applications. We focus on applications that use frameworks such as Ruby on Rails, Django or Spring. These frameworks are RESTful, enforce the Model-View-Controller architecture, and use Object Relational Mapping libraries to manipulate data. We developed a formal model for data stores and data store manipulation, including access control. We developed a translation of these models to formulas in First Order Logic (FOL) that allows for verification of data model invariants using off-the-shelf FOL theorem provers. In addition, we developed a method for extracting these models from existing applications implemented in Ruby on Rails. Our results demonstrate that our approach is applicable to real world applications, it is able to discover previously unknown bugs, and it does so within minutes on commonly available hardware