Digital Ecosystems: Self-Organisation of Evolving Agent Populations

A primary motivation for our research in Digital Ecosystems is the desire to exploit the self-organising properties of biological ecosystems. Ecosystems are thought to be robust, scalable architectures that can automatically solve complex, dynamic problems. Self-organisation is perhaps one of the most desirable features in the systems that we engineer, and it is important for us to be able to measure self-organising behaviour. We investigate the self-organising aspects of Digital Ecosystems, created through the application of evolutionary computing to Multi-Agent Systems (MASs), aiming to determine a macroscopic variable to characterise the self-organisation of the evolving agent populations within. We study a measure for the self-organisation called Physical Complexity; based on statistical physics, automata theory, and information theory, providing a measure of information relative to the randomness in an organism's genome, by calculating the entropy in a population. We investigate an extension to include populations of variable length, and then built upon this to construct an efficiency measure to investigate clustering within evolving agent populations. Overall an insight has been achieved into where and how self-organisation occurs in our Digital Ecosystem, and how it can be quantified.Comment: 5 pages, 5 figures, ACM Management of Emergent Digital EcoSystems (MEDES) 200

Ecosystem-Oriented Distributed Evolutionary Computing

We create a novel optimisation technique inspired by natural ecosystems, where the optimisation works at two levels: a first optimisation, migration of genes which are distributed in a peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. We consider from the domain of computer science distributed evolutionary computing, with the relevant theory from the domain of theoretical biology, including the fields of evolutionary and ecological theory, the topological structure of ecosystems, and evolutionary processes within distributed environments. We then define ecosystem- oriented distributed evolutionary computing, imbibed with the properties of self-organisation, scalability and sustainability from natural ecosystems, including a novel form of distributed evolu- tionary computing. Finally, we conclude with a discussion of the apparent compromises resulting from the hybrid model created, such as the network topology.Comment: 8 pages, 5 figures. arXiv admin note: text overlap with arXiv:1112.0204, arXiv:0712.4159, arXiv:0712.4153, arXiv:0712.4102, arXiv:0910.067

Validation of data analysis routines for a thermal probe apparatus using numerical data sets

Most thermal properties of construction materials used in the analysis of building performance have been measured under laboratory conditions, using a guarded hot box or hot plate apparatus. As a consequence, these properties seldom reflect the impact of actual conditions (especially moisture content) on the values of conductivity and diffusivity. Hence there is a need to develop techniques that allow to take into account local conditions, and measure building material properties in situ. One option available is the use of a thermal probe. The thermal probe technique is based on creating a line source in a material sample, and measuring the temperature rise in the sample in reaction to heat being applied. Obviously the data analysis routines used to calculate thermal conductivity and thermal diffusivity based on the temperature rise observed are crucial to the success of the technique. Transient thermal simulation of a of a model representing a line source in an infinite material sample has been used to generate a set of numerical data sets to validate analysis routines in conjunction with an experimental thermal probe apparatus. Findings show that by careful application of these routines, a close agreement with simulation input values can be achieved, with errors of less than one percent. This validates the analysis routines and provides a deeper appreciation of the theoretical behaviour of a thermal probe

Digital Ecosystems: Ecosystem-Oriented Architectures

We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures where the word ecosystem is more than just a metaphor.Comment: 39 pages, 26 figures, journa

An assessment of the potential returns of energy certificates for the UK household sector

Purpose – This article seeks to investigate the interconnections between the expectations of the impact of energy certificates issued within the UK domestic building sector through the Energy Performance of Buildings Directive (EPBD) and the actual number and financial implications of the energy saving measures (ESMs) achieved. Design/methodology/approach – The methodology uses two previously published surveys and compares these with a third independent survey by the authors focusing upon the discrepancies between planned action and implemented action, introducing the term human factor element (hfe). Findings – The article concludes that annual carbon savings arising from implementation of the Energy Performance Certificate (EPC) may be as low as 73.4?ktC over the five year term of the Kyoto Protocol even though 44 per cent of energy saving measure costs of £200 million are recouped within the same time period and savings will continue for up to 40 years. Achieving annual savings of only 14.7?ktC by 2010, such a figure represents a mere 0.3 per cent of the annual domestic 4.8?MtC savings announced by the government in its 2006 Climate Change Programme. Practical implications – Since the principal determinant in the uptake of ESMs is initial cost, it is considered that the EPBD is likely to remain an under-performing instrument in the promotion of energy sufficiency until such time as other complementary provisions are introduced. Originality/value – Sheds light upon the likely financial impact upon energy efficiency in domestic buildings by energy certificates

The emergence of knowledge exchange: an agent-based model of a software market.

We investigate knowledge exchange among commercial organisations, the rationale behind it and its effects on the market. Knowledge exchange is known to be beneficial for industry, but in order to explain it, authors have used high level concepts like network effects, reputation and trust. We attempt to formalise a plausible and elegant explanation of how and why companies adopt information exchange and why it benefits the market as a whole when this happens. This explanation is based on a multi-agent model that simulates a market of software providers. Even though the model does not include any high-level concepts, information exchange naturally emerges during simulations as a successful profitable behaviour. The conclusions reached by this agent-based analysis are twofold: (1) A straightforward set of assumptions is enough to give rise to exchange in a software market. (2) Knowledge exchange is shown to increase the efficiency of the marketAgent-based Computational Economics, adaptive behaviour, knowledge sharing, market efficiency