A multi-agent-based evolution model of innovation networks in dynamic environments

An innovation network can be considered as a complex adaptive system with evolution affected by dynamic environments. This paper establishes a multi-agent-based evolution model of innovation networks under dynamic settings through computational and logical modeling, and a multi-agent system paradigm. This evolution model is composed of several sub-models of agents' knowledge production by independent innovations in dynamic situations, knowledge learning by cooperative innovations covering agents' heterogeneities, decision-making for innovation selections, and knowledge update considering decay factors. On the basis of above-mentioned sub-models, an evolution rule for multi-agent based innovation network system is given. The proposed evolution model can be utilized to simulate and analyze different scenarios of innovation networks in various dynamic environments and support decision-making for innovation network optimization.

Managing the transition to work: the role of the planning network in British town planning education

The development of town planning education in the United Kingdom can be traced back over at least sixty years and has always enjoyed a close relationship with practitioners, employers and the professional body, the Royal Town Planning Institute (RTPI). In order to ensure an intake of sufficient quality to a growing profession, the Institute offered its own exams until the 1980s and then initiated the current system of accrediting both undergraduate and postgraduate programmes of study. This system of accreditation emphasises the importance of relevant knowledge, skills and values as well as core and specialised studies. The vocational nature of town planning requires that graduates have the breadth of understanding as well as the practical skills in order to practice effectively. Thus accredited courses have over time developed strong links with employers and practitioners. Rapid developments in the scope and range of planning, and the skills needed to work in it, have reflected changes in public policy and growing number of agencies concerned with the built environment. The system of regular quinquennial visits to accredit courses has helped ensure that this acceptance of change has become part of the culture of planning schools.

The metamorphosis of authority: a case study of the Aga Khan Development Network and the Ismaili Imamate

This research is a study of modern developments of the institutions of the Nizārī Ismaili imamate during the time of the present Ismaili Imam, Shāh Karīm al-Ḥusaynī, Aga Khan IV, as the 49th hereditary living Imam of Shiʿi Nizārī Ismaili Muslims, particularly addressing the formation of the Aga Khan Development Network (AKDN) and the functions of the Community institutions. Using the case study of the Aga Khan Development Network and the Nizārī Ismaili imamate, this research demonstrates that the three ideal types of authority as proposed by Weber, namely the traditional, charismatic and legal-bureaucratic types, are not sufficient to explain the dynamics of authority among Muslims. This is partly due to Weber’s belief in the uniqueness of Western civilisation, which is a product of his thesis on Protestant Ethics and partly because his ideal typical system does not work in the case of the Muslim societies. The Ismaili imamate with its multifarious institutions in contemporary times is the most suitable counter-example by which to powerfully demonstrate that Weberian models of authority fail to explain this phenomenon and it would indeed appear as a paradoxical institution if viewed with Weberian theses. The Ismaili imamate in contemporary times represents a paradigm shift and a transmutation not only as regards the Weberian models but also when viewed from inside the tradition of Shiʿi Muslim history. This evolutionary leap forward, which has been crystallised over the course of the past half a century, in the Ismaili imamate suggests the development of a new form of authority which is unprecedented. There are clearly various elements in this form of authority which could be discerned as rooted in tradition and history; however the distinctive elements of this new form of authority give it a defining and exciting dimension. There are several qualities which are peculiar to the contemporary condition of the Ismaili imamate and its style of leadership which are distinctive. Most importantly, while some central features, like succession by way of designation (naṣṣ) has not changed, there is one overarching quality which can best capture all these elements and that is the transmutation of the Ismaili imamate from the person of the Imam into the office of imamate and thus we are now facing the institutionalisation of the imamate and the office being the embodiment of the authority of the Imam. I have described this new development as a metamorphosis of the authority because it gives an entirely new form and content to the previously familiar concept of authority in the Shiʿi Ismaili Muslim tradition.

Urban transformations and rail stations system - the study case of Naples

The aim of this study is to give an interpretation of the urban transformations connected to rail transit system investments; in particular the main research goal is to analyze and give a methodological support for the urban transformation phenomena government in the rail transit stations areas. The article proposes an empirical studies comparative analysis and an application in the Naples urban area, in which a new rail transit network has been developed. In particular the socio-economic transit impacts on the urban system are measured and interpretated with the support of a GIS; therefore an application of the node-place interpretative model (Bertolini 1999) is proposed in order to support transit–land use planning processes in the stations areas.

Network mechanisms of intentional learning

The ability to learn new tasks rapidly is a prominent characteristic of human behaviour. This ability relies on flex- ible cognitive systems that adapt in order to encode temporary programs for processing non-automated tasks. Previous functional imaging studies have revealed distinct roles for the lateral frontal cortices (LFCs) and the ven- tral striatum in intentional learning processes. However, the human LFCs are complex; they house multiple dis- tinct sub-regions, each of which co-activates with a different functional network. It remains unclear how these LFC networks differ in their functions and how they coordinate with each other, and the ventral striatum, to support intentional learning. Here, we apply a suite of fMRI connectivity methods to determine how LFC networks activate and interact at different stages of two novel tasks, in which arbitrary stimulus-response rules are learnt either from explicit instruction or by trial-and-error. We report that the networks activate en masse and in synchrony when novel rules are being learnt from instruction. However, these networks are not homogeneous in their functions; instead, the directed connectivities between them vary asymmetrically across the learning timecourse and they disengage from the task sequentially along a rostro-caudal axis. Furthermore, when negative feedback indicates the need to switch to alternative stimulus–response rules, there is additional input to the LFC networks from the ventral striatum. These results support the hypotheses that LFC networks interact as a hierarchical system during intentional learning and that signals from the ventral striatum have a driving influence on this system when the internal program for processing the task is updated.

Dynamic Network Mechanisms of Relational Integration

A prominent hypothesis states that specialized neural modules within the human lateral frontopolar cortices (LFPCs) support “relational integration” (RI), the solving of complex problems using inter-related rules. However, it has been proposed that LFPC activity during RI could reflect the recruitment of additional “domain-general” resources when processing more difficult problems in general as opposed to RI specifi- cally. Moreover, theoretical research with computational models has demonstrated that RI may be supported by dynamic processes that occur throughout distributed networks of brain regions as opposed to within a discrete computational module. Here, we present fMRI findings from a novel deductive reasoning paradigm that controls for general difficulty while manipulating RI demands. In accordance with the domain- general perspective, we observe an increase in frontoparietal activation during challenging problems in general as opposed to RI specifically. Nonetheless, when examining frontoparietal activity using analyses of phase synchrony and psychophysiological interactions, we observe increased network connectivity during RI alone. Moreover, dynamic causal modeling with Bayesian model selection identifies the LFPC as the effective connectivity source. Based on these results, we propose that during RI an increase in network connectivity and a decrease in network metastability allows rules that are coded throughout working memory systems to be dynamically bound. This change in connectivity state is top-down propagated via a hierarchical system of domain-general networks with the LFPC at the apex. In this manner, the functional network perspective reconciles key propositions of the globalist, modular, and computational accounts of RI within a single unified framework.