113 research outputs found
On Agent-Based Software Engineering
Agent-based computing represents an exciting new synthesis both for Artificial Intelligence (AI) and, more generally, Computer Science. It has the potential to significantly improve the theory and the practice of modeling, designing, and implementing computer systems. Yet, to date, there has been little systematic analysis of what makes the agent-based approach such an appealing and powerful computational model. Moreover, even less effort has been devoted to discussing the inherent disadvantages that stem from adopting an agent-oriented view. Here both sets of issues are explored. The standpoint of this analysis is the role of agent-based software in solving complex, real-world problems. In particular, it will be argued that the development of robust and scalable software systems requires autonomous agents that can complete their objectives while situated in a dynamic and uncertain environment, that can engage in rich, high-level social interactions, and that can operate within flexible organisational structures
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Evolving structure-function mappings in cognitive neuroscience using genetic programming
A challenging goal of psychology and neuroscience is to map cognitive functions onto neuroanatomical structures. This paper shows how computational methods based upon evolutionary algorithms can facilitate the search for satisfactory mappings by efficiently combining constraints from neuroanatomy and physiology (the structures) with constraints from behavioural experiments (the functions). This methodology involves creation of a database coding for known neuroanatomical and physiological constraints, for mental programs made of primitive cognitive functions, and for typical experiments with their behavioural results. The evolutionary algorithms evolve theories mapping structures to functions in order to optimize the fit with the actual data. These theories lead to new, empirically testable predictions. The role of the prefrontal cortex in humans is discussed as an example. This methodology can be applied to the study of structures or functions alone, and can also be used to study other complex systems.
(This article does not exactly replicate the final version published in the Journal of Swiss Psychology. It is not a copy of the original published article and is not suitable for citation.
Agent-Based Computing: Promise and Perils
Agent-based computing represents an exciting new synthesis both for Artificial Intelligence (AI) and, more generally, Computer Science. It has the potential to significantly improve the theory and practice of modelling, designing and implementing complex systems. Yet, to date, there has been little systematic analysis of what makes an agent such an appealing and powerful conceptual model. Moreover, even less effort has been devoted to exploring the inherent disadvantages that stem from adopting an agent-oriented view. Here both sets of issues are explored. The standpoint of this analysis is the role of agent-based software in solving complex, real-world problems. In particular, it will be argued that the development of robust and scalable software systems requires autonomous agents that can complete their objectives while situated in a dynamic and uncertain environment, that can engage in rich, high-level social interactions, and that can operate within flexible organisational structures
Line Graphs of Weighted Networks for Overlapping Communities
In this paper, we develop the idea to partition the edges of a weighted graph
in order to uncover overlapping communities of its nodes. Our approach is based
on the construction of different types of weighted line graphs, i.e. graphs
whose nodes are the links of the original graph, that encapsulate differently
the relations between the edges. Weighted line graphs are argued to provide an
alternative, valuable representation of the system's topology, and are shown to
have important applications in community detection, as the usual node partition
of a line graph naturally leads to an edge partition of the original graph.
This identification allows us to use traditional partitioning methods in order
to address the long-standing problem of the detection of overlapping
communities. We apply it to the analysis of different social and geographical
networks.Comment: 8 Pages. New title and text revisions to emphasise differences from
earlier paper
A Guide for Newcomers to Agent-Based Modeling in the Social Sciences
This guide provides pointers to introductory readings, software, and other materials to help newcomers become acquainted with agent-based modeling in the social sciences. Related work can be accessed at: http://www.econ.iastate.edu/tesfatsi/ace.htmagent-based modeling; social sciences
Hierarchical modularity in human brain functional networks
The idea that complex systems have a hierarchical modular organization
originates in the early 1960s and has recently attracted fresh support from
quantitative studies of large scale, real-life networks. Here we investigate
the hierarchical modular (or "modules-within-modules") decomposition of human
brain functional networks, measured using functional magnetic resonance imaging
(fMRI) in 18 healthy volunteers under no-task or resting conditions. We used a
customized template to extract networks with more than 1800 regional nodes, and
we applied a fast algorithm to identify nested modular structure at several
hierarchical levels. We used mutual information, 0 < I < 1, to estimate the
similarity of community structure of networks in different subjects, and to
identify the individual network that is most representative of the group.
Results show that human brain functional networks have a hierarchical modular
organization with a fair degree of similarity between subjects, I=0.63. The
largest 5 modules at the highest level of the hierarchy were medial occipital,
lateral occipital, central, parieto-frontal and fronto-temporal systems;
occipital modules demonstrated less sub-modular organization than modules
comprising regions of multimodal association cortex. Connector nodes and hubs,
with a key role in inter-modular connectivity, were also concentrated in
association cortical areas. We conclude that methods are available for
hierarchical modular decomposition of large numbers of high resolution brain
functional networks using computationally expedient algorithms. This could
enable future investigations of Simon's original hypothesis that hierarchy or
near-decomposability of physical symbol systems is a critical design feature
for their fast adaptivity to changing environmental conditions
Federated Embedded Systems – a review of the literature in related fields
This report is concerned with the vision of smart interconnected objects, a vision that has attracted much attention lately. In this paper, embedded, interconnected, open, and heterogeneous control systems are in focus, formally referred to as Federated Embedded Systems. To place FES into a context, a review of some related research directions is presented. This review includes such concepts as systems of systems, cyber-physical systems, ubiquitous
computing, internet of things, and multi-agent systems. Interestingly, the reviewed fields seem to overlap with each other in an increasing number of ways
A socio-technical perspective on the future Vessel Traffic Services
Autonomy is expected to cause significant changes to the Maritime Traffic System (MTS). The Vessel Traffic Services (VTS) is a control system in the MTS and will be affected by new interactions caused by autonomy. The paper proposes a proactive approach in discussing the future VTS. The paper renders the historical development of socio-technical systems theory and argues for systemic evaluation of internal and external consequences of changes in the design of the future VTS. A democratic process to involve people from the various levels of the VTS organisation with different competencies is suggested. To evaluate the consequences of change, a systemic internal and external approach is suggested. For discussing internal consequences, a levelled socio-technical systems model is adapted and applied. External consequences are suggested to be discussed by applying design principles of system-of-systems to understand the interplay between VTS and the MTS
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FabSim3: An automation toolkit for verified simulations using high performance computing
A common feature of computational modelling and simulation research is the need to perform many
tasks in complex sequences to achieve a usable result. This will typically involve tasks such as preparing
input data, pre-processing, running simulations on a local or remote machine, post-processing, and
performing coupling communications, validations and/or optimisations. Tasks like these can involve
manual steps which are time and effort intensive, especially when it involves the management of large
ensemble runs. Additionally, human errors become more likely and numerous as the research work
becomes more complex, increasing the risk of damaging the credibility of simulation results. Automation
tools can help ensure the credibility of simulation results by reducing the manual time and effort
required to perform these research tasks, by making more rigorous procedures tractable, and by reducing
the probability of human error due to a reduced number of manual actions. In addition, efficiency
gained through automation can help researchers to perform more research within the budget and effort
constraints imposed by their projects.
This paper presents the main software release of FabSim3, and explains how our automation toolkit
can improve and simplify a range of tasks for researchers and application developers. FabSim3 helps
to prepare, submit, execute, retrieve, and analyze simulation workflows. By providing a suitable level
of abstraction, FabSim3 reduces the complexity of setting up and managing a large-scale simulation
scenario, while still providing transparent access to the underlying layers for effective debugging.
The tool also facilitates job submission and management (including staging and curation of files
and environments) for a range of different supercomputing environments. Although FabSim3 itself is
application-agnostic, it supports a provably extensible plugin system where users automate simulation
and analysis workflows for their own application domains. To highlight this, we briefly describe a
selection of these plugins and we demonstrate the efficiency of the toolkit in handling large ensemble
workflows.EPSRC under grant agreement EP/W007711/1, as well as by the VECMA and HiDALGO projects, which have
received funding from the European Union Horizon 2020 research and innovation programme under grant agreement nos 800925 and
824115. In addition, FabFlee was supported by the ITFLOWS project and FabCovid19 by the STAMINA project, both of which have received
funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 882986 and No 883441
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