Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

System upgrade: realising the vision for UK education

A report summarising the findings of the TEL programme in the wider context of technology-enhanced learning and offering recommendations for future strategy in the area was launched on 13th June at the House of Lords to a group of policymakers, technologists and practitioners chaired by Lord Knight. The report – a major outcome of the programme – is written by TEL director Professor Richard Noss and a team of experts in various fields of technology-enhanced learning. The report features the programme’s 12 recommendations for using technology-enhanced learning to upgrade UK education

AI and Legal Scholarship : Reflections on Evolution and Influences

Leading Legal Disruption: Artificial Intelligence and a Toolkit for Lawyers and the Law is designed to challenge lawyers with the practical implications that emerging technologies will have on delivering legal services and thinking about legal issues to navigate their digital transformation. By inviting thought leaders across the world and in different disciplines, ranging from privacy, contract law, and torts to governance and policy, this book goes beyond abstract and general philosophical observations on matters that concern practitioners. This practical approach has generated a wide range of global perspectives, which are refreshingly novel and timely for what are increasingly global issues. The development and deployment of AI technologies present an excellent opportunity for humanity, where its positive impact can already be seen in transportation, health, finance, law, and other sectors. Autonomous vehicles and the prediction of COVID-19 spread present only a fraction of AI\u27s potential. AI is already automating various intellectual tasks that traditionally believed could only be carried out by human legal professionals, such as predicting court outcomes, legal drafting, contract review, case summarization, and legal research. For some, it was a surprise to read a report by McKinsey that estimated that 23% of work done by lawyers could already be automated by existing technology

Modeling economic systems as locally-constructive sequential games

Real-world economies are open-ended dynamic systems consisting of heterogeneous interacting participants. Human participants are decision-makers who strategically take into account the past actions and potential future actions of other participants. All participants are forced to be locally constructive, meaning their actions at any given time must be based on their local states; and participant actions at any given time affect future local states. Taken together, these essential properties imply real-world economies are locally-constructive sequential games. This paper discusses a modeling approach, Agent-based Computational Economics, that permits researchers to study economic systems from this point of view. ACE modeling principles and objectives are first concisely presented and explained. The remainder of the paper then highlights challenging issues and edgier explorations that ACE researchers are currently pursuing

Steps to a Sustainable Mind : Explorations into the Ecology of Mind and Behaviour

This transdisciplinary doctoral thesis presents various theoretical, methodological and empirical approaches that together form an ecological approach to the study of social sciences. The key argument follows: to understand how sustainable behaviours and cultures may emerge, and how their development can be facilitated, we must further learn how behaviours emerge as a function of the person and the material and social environment. Furthermore, in this thesis the sustainability crises are framed as sustain-ability crises. We must better equip our cultures with abilities to deal with the complexity and uncertainty of socio-ecological systems, and use these cultural skillsets to survive in and adapt to an increasingly unpredictable world. This thesis employs a plurality of ecological social sciences and related methodologies—such as ecological psychology, ecological rationality and agent-based modelling—to enlighten the question of how the collective adoption of sustainable behaviours can be leveraged, particularly by changing the affordances in the material environment. What is common to these ecological approaches is the appreciation of ‘processes’ over ‘products’: we must understand the various processes through which sustainable forms of behaviour or decision-making emerge to truly locate leverage points in social systems. Finally, this thesis deals extensively with uncertainty in complex systems. It proposes that we can look to local and traditional knowledge in learning how to deal adaptively with uncertainty.Tässä poikkitieteellisessä väitöskirjassa esitetään lukuisia teoreettisia, metodologisia ja empiirisiä näkökulmia, jotka yhdessä muodostavat ekologisen lähestymistavan sosiaalitieteelliseen tutkimukseen. Tutkielman keskeinen argumentti on: jotta voimme oppia, miten kestävät käyttäytymismallit ja kulttuurit syntyvät ja miten niiden kehitystä voi edesauttaa, meidän täytyy ymmärtää, miten ne syntyvät ihmisen ja (materiaalisen sekä sosiaalisen) ympäristön funktiona. Tässä väitöskirjassa kestävyyskriisiä tulkitaan käyttäytymistieteellisestä ja kulttuurievoluution näkökulmasta. Sopeutuaksemme yhä hankalammin ennustettavaan tulevaisuuteen, kulttuurimme on opittava ja mukauduttava hallitsemaan epävarmuutta sekä tietoisesti ohjaamaan kulttuurievoluutiota kestävään suuntaan. Tässä väitöskirjassa hyödynnetään lukuisia teoreettisia ja metodologisia tulokulmia, esimerkiksi ekologista psykologiaa, ekologista rationaalisuutta sekä agenttipohjaista mallinnusta. Yhdessä näiden tulokulmien kautta pyritään ymmärtämään, miten voimme paikantaa yhteiskunnista vipupisteitä kestäviin käyttäytymismuutoksiin esimerkiksi materiaalista ympäristöä muokkaamalla. Väitöskirjan tulokulma painottaa erityisesti käyttäytymismuutosten taustalla olevien prosessien tulkintaa: jotta voimme ymmärtää, miten kestävät käyttäytymismallit tai päätöksenteot syntyvät, meidän on ymmärrettävä miten ne syntyvät lukuisten monimutkaisten ja kytkennäisten sosiaalisten prosessien kautta. Tässä väitöskirjassa tutkitaan myös epävarmuutta kompleksisissa järjestelmissä. Väitöskirjassa esitetään, että paikallisesta ja perinteisestä tietämyksestä voi olla paljon opittavaa sopeutuessamme epävarmaan tulevaisuuteen

A context-aware framework for collaborative activities in pervasive communities

Pervasive environments involve the interaction of users with the objects that surround them and also other participants. In this way, pervasive communities can lead the user to participate beyond traditional pervasive spaces, enabling the cooperation among groups taking into account not only individual interests, but also the collective and social context. In this study, the authors explore the potential of using context-aware information in CSCW application in order to support collaboration in pervasive environments. In particular this paper describes the approach used in the design and development of a context-aware framework utilizing users' context information interpretation for behaviour adaptation of collaborative applications in pervasive communities