44 research outputs found
Inferring Best Strategies from the Aggregation of Information from Multiple Agents: The Cultural Approach
Although learning in MAS is described as a collective experience, most of the times its modeling draws solely or mostly on the results of the interaction between the agents.
This abruptly contrasts with our everyday experience where learning relies, to a great extent, on a large stock of already codified knowledge rather than on the direct interaction among the agents.
If in the course human history this reliance on already codified knowledge had a significant importance, especially since the discovery of writing, during the last decade the size and availability of this stock has increased notably because of the Internet.
Even more, humanity has endowed itself with institutions and organizations devoted to fulfill the role of codifying, preserving and diffusing knowledge since its early days.
Cultural Algorithms are one of the few cases where the modeling of this process, although in a limited way, has been attempted.
However, even in this case, the modeling lacks some of the characteristics that have made it so successful in human populations, notably its frugality in learning only from a rather small subset of the population and a discussion of its dynamics in terms of hypothesis generation and falsification and the relationship between adaptation and discovery.
A deep understanding of this process of collective learning, in all its aspects of generalization and re-adoption of this collective and distilled knowledge, together with its diffusion is a key element to understand how human communities function and how a mixed community of humans and electronic agents could effectively learn. And this is more important now than ever because this process has become not only global and available to large populations but also has largely increased its speed.
This research aims to contribute to cover this gap, elucidating on the frugality of the mechanism while mapping it in a framework characterized by a variable level of complexity of knowledge.
Also seeks to understand the macro dynamics resulting from the micro mechanisms and strategies chosen by the agents.
Nevertheless, as any exercise based on modeling, it portrays a stylized description of reality that misses important points and significant aspects of the real behavior. In this case, while we will focus on individual learning and on the process of generalization and ulterior re-use of these generalizations, learning from other agents is notably absent. We believe however, that this choice contributes to make our model easier to understand and easier to expose the causality relationships emerging from our simulation exercises without sacrificing any significant result
Inferring Best Strategies from the Aggregation of Information from Multiple Agents: The Cultural Approach
Although learning in MAS is described as a collective experience, most of the times its modeling draws solely or mostly on the results of the interaction between the agents.
This abruptly contrasts with our everyday experience where learning relies, to a great extent, on a large stock of already codified knowledge rather than on the direct interaction among the agents.
If in the course human history this reliance on already codified knowledge had a significant importance, especially since the discovery of writing, during the last decade the size and availability of this stock has increased notably because of the Internet.
Even more, humanity has endowed itself with institutions and organizations devoted to fulfill the role of codifying, preserving and diffusing knowledge since its early days.
Cultural Algorithms are one of the few cases where the modeling of this process, although in a limited way, has been attempted.
However, even in this case, the modeling lacks some of the characteristics that have made it so successful in human populations, notably its frugality in learning only from a rather small subset of the population and a discussion of its dynamics in terms of hypothesis generation and falsification and the relationship between adaptation and discovery.
A deep understanding of this process of collective learning, in all its aspects of generalization and re-adoption of this collective and distilled knowledge, together with its diffusion is a key element to understand how human communities function and how a mixed community of humans and electronic agents could effectively learn. And this is more important now than ever because this process has become not only global and available to large populations but also has largely increased its speed.
This research aims to contribute to cover this gap, elucidating on the frugality of the mechanism while mapping it in a framework characterized by a variable level of complexity of knowledge.
Also seeks to understand the macro dynamics resulting from the micro mechanisms and strategies chosen by the agents.
Nevertheless, as any exercise based on modeling, it portrays a stylized description of reality that misses important points and significant aspects of the real behavior. In this case, while we will focus on individual learning and on the process of generalization and ulterior re-use of these generalizations, learning from other agents is notably absent. We believe however, that this choice contributes to make our model easier to understand and easier to expose the causality relationships emerging from our simulation exercises without sacrificing any significant result
Understanding Innovation as a Collaborative, Co-Evolutionary Process
La innovació, que ha estat durant molt de temps el resultat, a vegades heroic, de la tasca d'un emprenedor solitari, està esdevenint progressivament una tasca col·lectiva que troba una descripció més acurada quan es presenta com el resultat d'un procés complex amb múltiples actors. Aquesta tesi vol explorar aquest aspecte col·lectiu de la innovació, tot aprofundint en dues línies de recerca. Una, que utilitza el modelatge basat en agents per a la creació de model teòrics. L'altre, que es basa en l'ús de l'anàlisi qualitatiu per a esbrinar algunes de les claus d'unes organitzacions ‐els Living Labs ‐ que cerquen involucrar els usuaris en el procés d'innovació. Ara bé, malgrat presentem la innovació com un procés obert, aquesta entesa com un procés tancat sembla també tenir èxit. De fet, tant els telèfons mòbils molt simples o molt complexos, semblen seguir aquest enfocament. En quines condicions el procés d'innovació es beneficia de ser un procés obert i quan és possible obtenir millors resultats retenint el control de la totalitat del procés, és la nostra primera pregunta de recerca. D'altra banda, aquest procés de col·laboració, característic d'un enfocament obert, és considerat normalment a un nivell micro com el resultat de la interacció diàdica entre agents. Existeix però, un altre nivell, un nivell macro que ve caracteritzat per la funció d'institucions com les Escoles de Negocis, que juguen un paper important en destil·lar les millors pràctiques i crear hipòtesis a partir d'elles que si es revelen exitoses seran adoptades per la totalitat dels agents. La comprensió del funcionament d'aquest procés, del nombre de casos que cal considerar i de quan extensius han de ser, entendre fins a quin punt les empreses poden confiar en l'assessorament de les Escoles de Negoci i quan es necessari aventurar‐se en l'exploració de noves possibilitats, és també quelcom necessari per a caracteritzar la innovació com un procés col·lectiu. Malauradament, la nostra comprensió dels mecanismes col·laboratius és encara escassa. Sabem però, que la innovació ja no és quelcom exclusiu dels laboratoris d'I+D o d'organitzacions capdavanteres, sinó que els usuaris juguen no solament un paper rellevant sinó que són percebuts com a actors amb un gran potencial. Els Living Labs és una de les tentatives per proporcionar estructura i governança a la involucració dels usuaris en el procés d'innovació. En aquest aspecte, examinarem quina és la contribució d'aquests usuaris i com els Living Labs busquen capturar‐ne el seu coneixement i aplicar‐lo i quant tenen èxit en aquest procés.La innovación, que se ha presentado muchas veces como el resultado de un proceso, muchas veces heroico, de emprendedores excepcionales, se está convirtiendo de una forma progresiva en un proceso colectivo que se describe con más acierto cuando se presenta como el resultado de un proceso complejo con multitud de actores. Esta tesis, pretende explorar este aspecto colectivo del proceso de innovación, profundizando en dos líneas de investigación. Una que utiliza el modelado basado en agentes para la construcción de modelos teóricos. Otra que se basa en el análisis cualitativo para profundizar en las claves de unas organizaciones ¬los Living Labs ‐ que buscan involucrar a los usuarios en los procesos de innovación. Ahora bien, a pesar de que la innovación se presente como un proceso abierto, ésta entendida como un proceso cerrado, parece también tener éxito. De hecho, los teléfonos móviles muy simples o muy complejos, parecen seguir este enfoque. En qué condiciones el proceso de innovación se beneficia de ser un proceso abierto y cuando es posible obtener mejores resultados reteniendo el control de la totalidad del proceso, es nuestra primera pregunta de investigación. Por otro lado, este proceso de colaboración, característico de un enfoque abierto, es considerado normalmente a un nivel micro, como el resultado de la interacción diádica entre agentes. Existe pero, otro nivel, un nivel macro, caracterizado por la función de instituciones como las Escuelas de Negocios, que juegan un papel importante destilando las mejores prácticas y creando hipótesis a partir de ellas que si se revelan exitosas serán masivamente adoptadas. La comprensión del funcionamiento de este proceso, del número de casos a considerar y de su extensión, comprender hasta qué punto las empresas pueden confiar en el asesoramiento de las Escuelas de Negocios y cuando es necesario aventurarse en un proceso de exploración de nuevas posibilidades, es también algo imprescindible para caracterizar la innovación como un proceso colectivo. Desgraciadamente nuestra comprensión de los mecanismos colaborativos en la innovación es aún escasa. Sin embargo sabemos que la innovación ya no es algo exclusivo de los laboratorios de I+D o de grandes empresas, los usuarios juegan no sólo un papel relevante sino que son percibidos como actores con un alto potencial. Los Living Labs es una de las tentativas que buscan proporcionar estructura y gobierno a la involucración de los usuarios en el proceso de innovación. En este aspecto, examinaremos cuál es la contribución de los usuarios, cómo los Living Labs buscan capturar su conocimiento y aplicarlo y cuando tienen éxito en su intento.Innovation, which used to be the result of a single, sometimes heroic, entrepreneur, is progressively turning into a collaborative endeavor, better described as the result of a complex process with multiple actors. This thesis aims to explore this collaborative aspect of innovation by digging into two strands of research. One uses Agent‐Based Modeling to create theoretical models, where the other one uses qualitative analysis to devise some insights from organizations ‐Living Labs ‐that aim to involve users in innovation. In addition to understanding innovation as an open process, a closed one seems sometimes to be equally successful. In fact, very simple and very complex mobile phones seem to follow this later approach. Under what conditions innovation benefits from being open and when better results can be obtained from retaining control of the whole process is our first research question. This process of collaboration, characteristic of the open approach, is normally considered at a micro level, as a result of a dyadic interaction between agents. Nevertheless, there is a macro level characterized by institutions, such as Business Schools, that play an important role in uncovering Best Practices and building hypothesis that, if successful, will be adopted by the agents. Understanding how this process works; how many cases should be collected and how comprehensive they should be; how much companies can rely on the insights of Business Schools; and when it is necessary to engage in exploration, is also necessary when characterizing innovation as a collective process. The mechanisms of collaboration are, however, not all well‐understood. Innovation is no longer in the solely hands of R&D laboratories or even organizations, users play an increasingly significant role and are being perceived as holding vast potential. Living Labs is one attempt to provide structure and governance to user involvement in innovation. Here, we will examine what is the contribution of users, how Living Labs aim to capture relevant knowledge and apply it, and when and how this proves successful
A few misfits can Change the World
Rising inequality is a critical concern for societies worldwide, to the
extent that emerging high-growth economies such as China have identified common
prosperity as a central goal. However, the mechanisms by which digital
disruptions contribute to inequality and the efficacy of existing remedies such
as taxation, must be better understood. This is particularly true for the
implications of the complex process of technological adoption that requires
extensive social validation beyond weak ties and, how to trigger it in the
hyperconnected world of the 21st century.
This study aims to shed light on the implications of market evolutionary
mechanism from the lenses of technological adoption as a social process. Our
findings underscore the pivotal importance of connectivity in this process
while also revealing the limited effectiveness of taxation as a counterbalance
for inequality. Our research reveals that widespread cultural change is not a
prerequisite for technological disruption. The injection of a small cohort of
entrepreneurs - a few misfits - can expedite technology adoption even in
conservative, moderately connected societies and, change the world
Data ecosystems for protecting European citizens' digital rights
Purpose
This paper aims to spark a debate by presenting the need for developing data ecosystems in Europe that meet the social and public good while committing to democratic and ethical standards; suggesting a taxonomy of data infrastructures and institutions to support this need; using the case study of Barcelona as the flagship city trailblazing a critical policy agenda of smart cities to show the limitations and contradictions of the current state of affairs; and ultimately, proposing a preliminary roadmap for institutional and governance empowerment that could enable effective data ecosystems in Europe.
Design/methodology/approach
This paper draws on lessons learned in previous publications available in the sustainability (Calzada, 2018), regions (Calzada and Cowie, 2017; Calzada, 2019), Zenodo (Calzada and Almirall, 2019), RSA Journal (Calzada, 2019) and IJIS (Calzada, 2020) journals and ongoing and updated fieldwork about the Barcelona case study stemming from an intensive fieldwork action research that started in 2017. The methodology used in these publications was based on the mixed-method technique of triangulation via action research encompassing in-depth interviews, direct participation in policy events and desk research. The case study was identified as the most effective methodology.
Findings
This paper, drawing from lessons learned from the Barcelona case study, elucidates on the need to establish pan-European data infrastructures and institutions – collectively data ecosystems – to protect citizens’ digital rights in European cities and regions. The paper reveals three main priorities proposing a preliminary roadmap for local and regional governments, namely, advocacy, suggesting the need for city and regional networks; governance, requiring guidance and applied, neutral and non-partisan research in policy; and pan-European agencies, leading and mobilising data infrastructures and institutions at the European level.
Research limitations/implications
From the very beginning, this paper acknowledges its ambition, and thus its limitations and clarifies its attempt to provide just an overview rather than a deep research analysis. This paper presents several research limitations and implications regarding the scope. The paper starts by presenting the need for data ecosystems, then structures this need through two taxonomies, all illustrated through the Barcelona case study and finally, concludes with a roadmap consisting of three priorities. The paper uses previous published and ongoing fieldwork findings in Barcelona as a way to lead, and thus encourage the proliferation of more cases through Cities Coalition for Digital Rights (CCDR).
Practical implications
This paper presents practical implications for local and regional authorities of the CCDR network. As such, the main three priorities of the preliminary roadmap could help those European cities and regions already part of the CCDR network to establish and build operational data ecosystems by establishing a comprehensive pan-European policy from the bottom-up that aligns with the timely policy developments advocated by the European Commission. This paper can inspire policymakers by providing guidelines to better coordinate among a diverse set of cities and regions in Europe.
Social implications
The leading data governance models worldwide from China and the USA and the advent of Big Data are dramatically reshaping citizens’ relationship with data. Against this backdrop and directly influenced by the General Data Protection Regulation (GDPR), Europe has, perhaps, for the first time, spoken with its own voice by blending data and smart city research and policy formulations. Inquiries and emerging insights into the potential urban experiments on data ecosystems, consisting of data infrastructures and institutions operating in European cities and regions, become increasingly crucial. Thus, the main social implications are for those multi-stakeholder policy schemes already operating in European cities and regions.
Originality/value
In previous research, data ecosystems were not directly related to digital rights amidst the global digital geopolitical context and, more specifically, were not connected to the two taxonomies (on data infrastructures and institutions) that could be directly applied to a case study, like the one presented about Barcelona. Thus, this paper shows novelty and originality by also opening up (based on previous fieldwork action research) a way to take strategic action to establish a pan-European strategy among cities and regions through three specific priorities. This paper can ultimately support practice and lead to new research and policy avenues
Study protocol for a three-arm randomized controlled trial investigating the effectiveness, cost-utility, and physiological effects of a fully self-guided digital Acceptance and Commitment Therapy for Spanish patients with fibromyalgia
Objective Fibromyalgia (FM) is a prevalent pain syndrome with significant healthcare and societal costs. The aim of the SMART-FM-SP study is to determine the effectiveness, cost-utility, and physiological effects in patients with FM of a digital intervention (STANZA®) currently marketed in the United States, which delivers smartphone-based, fully self-guided Acceptance and Commitment Therapy (Digital ACT) for treating FM-related symptoms. Methods A single-site, parallel-group, superiority, randomized controlled trial (RCT) will be conducted, including a total of 360 adults diagnosed with FM. Individuals will be randomly allocated (1:1:1) to treatment as usual (TAU), to TAU plus 12 weeks of treatment with Digital ACT, or to TAU plus 12 weeks of treatment with digital symptom tracking (i.e. FibroST). Participants will be assessed at baseline, post-treatment, and 6-month follow-up. An intention-to-treat analysis using linear mixed models will be computed to analyze the effects of Digital ACT on functional impairment (primary outcome), as measured by the Fibromyalgia Impact Questionnaire Revised at 6 months from the inception of the treatment. Secondary outcomes include impression of change, symptoms of distress, pain catastrophising, quality of life, cost-utility, and selected biomarkers (cortisol and cortisone, immune-inflammatory markers, and FKBP5 gene polymorphisms). The role of ACT-related processes of change will be tested with path analyses. Conclusions This study is the first RCT that tests Digital ACT for Spanish patients with FM. Results will be important not only for patients and clinicians, but also for policy makers by examining the cost-utility of the app in a public healthcare context
Landscape and Roadmap of Future Internet and Smart Cities
FP7 Fireball coordination Action, http://www.fireball4smartcities.eu/This final D2.1 report forms a synthesis and further extension of the previousreports D1.2 [M6] and D1.2 [M12]. The key topics addressed in this reportreflect the key priorities of the WP2 and are: * Understanding the Smart City, providing state of the art and trends .FIREBALL understands Smart Cities as innovation ecosystems for the FutureInternet. The three areas of Smart Cities, Future Internet and Living Labsare explored including their interlinkages and how they can be exploited.This results into a mapping of the new landscape of Smart Cities and theFuture Internet. * Smart City case studies . Seven cases have been elaborated as a means toexplore and examine current developments, objectives, strategies in "smartcities" and establish collaboration between Smart Cities and the Eurocitiescommunity on one side and Future Internet and Living Labs on the other. * Collaboration models for Smart Cities innovation. In particular we focuson collaboration models that are fundamental to developing andimplementing common innovation activities of the three communitiesconstituting the FIREBALL domain: Smart Cities, Future Internet and Livinglabs. * Thematic Roadmap of Future Internet and Living Labs for SmartCities . This activity forms input for WP3 activities as well as to the Horizon2020 development process supported by the FISA group of Future InternetSupport Actions. The Roadmap activities also support the development of astrategy to implement collaboration models mentioned.The work regarding collaboration models relates strongly to the companionD1.2 (M12) report on Common Assets and the D1.3 (M12) report on Accessmechanisms. The D1.2 report identifies and describes smart cities, living labsand future Internet common assets, which is fundamental to the collaborationmodels mentioned. The D1.3 develops approaches to create access to theseassets and proposes sharing mechanisms.The topics addressed should be considered in close relation to the communitybuilding and collaborative activities that we have undertaken jointly with FIAand Eurocities communities since starting this project in 2010. Our intentionhas always been not only to produce reports but to play a proactive role inchanging the research and innovation landscape as regards Future Internet,Living Labs and Smart Cities
Smart Cities as Innovation Ecosystems sustained by the Future Internet
FIREBALL White paperThe White Paper focuses on how European cities are currently developing strategies towards becoming "smarter cities" and the lessons we can draw for the future. Such strategies are based on an assessment of the future needs of cities and innovative usages of ICTs embodied in the broadband Internet and Internet-based applications now and foreseen for the future. These strategies are also based on a new understanding of innovation, grounded in the concept of open innovation ecosystems, global innovation chains, and on citizens' empowerment for shaping innovation and urban development. This White Paper is one of the main outcomes of the FIREBALL project (www.fireball4smartcities.eu), a Coordination Action within the 7th Framework Programme for ICT, running in the period 2010-2012. The aim of FIREBALL is to bring together communities and stakeholders who are active in three areas: (1) research and experimentation on the Future Internet (FIRE); (2) open and user-driven innovation (Living Labs); and (3) urban development. The goal is to develop a common vision and a common view on how the different approaches, methodologies, policies and technologies in these areas can be aligned to boost innovation and socio-economic development of cities. The White Paper has explored the landscape of "smart cities" as environments of open and user driven innovation sustained by Future Internet technologies and services. Smart cities are also seen as environments enabled by advanced ICT infrastructure for testing and validating current Future Internet research and experimentation. Overall, the smart city is built upon a triangle of "City" - "Open Innovation Ecosystems" - "Future Internet" components. The White Paper explores also how cities and urban areas represent a critical mass when it comes to shaping the demand for advanced Internet-based services in large-scale testing and validation. Shaping this demand informs ongoing research, experimentation and deployment activities related to Future Internet testbeds, and helps establishing a dialogue between the different communities involved in the development of the future Internet and user-driven environments, to form partnerships and assess social and economic benefits and discovery of migration paths at early stages. Based on a holistic instead of technology merely driven perspective on smart cities, we consider necessary to revisit the concept of the Smart City itself. The concept of the smart city that emerges from FIREBALL can be summarized as follows: "The smart city concept is multi-dimensional. It is a future scenario (what to achieve), even more it is an urban development strategy (how to achieve it). It focuses on how (Internet-related) technologies enhance the lives of citizens. This should not be interpreted as drawing the smart city technology scenario. Rather, the smart city is how citizens are shaping the city in using this technology, and how citizens are enabled to do so. The smart city is about how people are empowered, through using technology, for contributing to urban change and realizing their ambitions. The smart city provides the conditions and resources for change. In this sense, the smart city is an urban laboratory, an urban innovation ecosystem, a living lab, an agent of change. Much less do we see a smart city in terms of a Ranking. This ranking is a moment in time, a superficial result of underlying changes, not the mechanism of transformation. The smart city is the engine of transformation, a generator of solutions for wicked problems, it is how the city is behaving smart.