135,878 research outputs found

    An Evolutionary Learning Approach for Adaptive Negotiation Agents

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    Developing effective and efficient negotiation mechanisms for real-world applications such as e-Business is challenging since negotiations in such a context are characterised by combinatorially complex negotiation spaces, tough deadlines, very limited information about the opponents, and volatile negotiator preferences. Accordingly, practical negotiation systems should be empowered by effective learning mechanisms to acquire dynamic domain knowledge from the possibly changing negotiation contexts. This paper illustrates our adaptive negotiation agents which are underpinned by robust evolutionary learning mechanisms to deal with complex and dynamic negotiation contexts. Our experimental results show that GA-based adaptive negotiation agents outperform a theoretically optimal negotiation mechanism which guarantees Pareto optimal. Our research work opens the door to the development of practical negotiation systems for real-world applications

    Survey of dynamic scheduling in manufacturing systems

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    Investigating biocomplexity through the agent-based paradigm.

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    Capturing the dynamism that pervades biological systems requires a computational approach that can accommodate both the continuous features of the system environment as well as the flexible and heterogeneous nature of component interactions. This presents a serious challenge for the more traditional mathematical approaches that assume component homogeneity to relate system observables using mathematical equations. While the homogeneity condition does not lead to loss of accuracy while simulating various continua, it fails to offer detailed solutions when applied to systems with dynamically interacting heterogeneous components. As the functionality and architecture of most biological systems is a product of multi-faceted individual interactions at the sub-system level, continuum models rarely offer much beyond qualitative similarity. Agent-based modelling is a class of algorithmic computational approaches that rely on interactions between Turing-complete finite-state machines--or agents--to simulate, from the bottom-up, macroscopic properties of a system. In recognizing the heterogeneity condition, they offer suitable ontologies to the system components being modelled, thereby succeeding where their continuum counterparts tend to struggle. Furthermore, being inherently hierarchical, they are quite amenable to coupling with other computational paradigms. The integration of any agent-based framework with continuum models is arguably the most elegant and precise way of representing biological systems. Although in its nascence, agent-based modelling has been utilized to model biological complexity across a broad range of biological scales (from cells to societies). In this article, we explore the reasons that make agent-based modelling the most precise approach to model biological systems that tend to be non-linear and complex

    From Social Simulation to Integrative System Design

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    As the recent financial crisis showed, today there is a strong need to gain "ecological perspective" of all relevant interactions in socio-economic-techno-environmental systems. For this, we suggested to set-up a network of Centers for integrative systems design, which shall be able to run all potentially relevant scenarios, identify causality chains, explore feedback and cascading effects for a number of model variants, and determine the reliability of their implications (given the validity of the underlying models). They will be able to detect possible negative side effect of policy decisions, before they occur. The Centers belonging to this network of Integrative Systems Design Centers would be focused on a particular field, but they would be part of an attempt to eventually cover all relevant areas of society and economy and integrate them within a "Living Earth Simulator". The results of all research activities of such Centers would be turned into informative input for political Decision Arenas. For example, Crisis Observatories (for financial instabilities, shortages of resources, environmental change, conflict, spreading of diseases, etc.) would be connected with such Decision Arenas for the purpose of visualization, in order to make complex interdependencies understandable to scientists, decision-makers, and the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c

    Models and metaphors: complexity theory and through-life management in the built environment

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    Complexity thinking may have both modelling and metaphorical applications in the through-life management of the built environment. These two distinct approaches are examined and compared. In the first instance, some of the sources of complexity in the design, construction and maintenance of the built environment are identified. The metaphorical use of complexity in management thinking and its application in the built environment are briefly examined. This is followed by an exploration of modelling techniques relevant to built environment concerns. Non-linear and complex mathematical techniques such as fuzzy logic, cellular automata and attractors, may be applicable to their analysis. Existing software tools are identified and examples of successful built environment applications of complexity modelling are given. Some issues that arise include the definition of phenomena in a mathematically usable way, the functionality of available software and the possibility of going beyond representational modelling. Further questions arising from the application of complexity thinking are discussed, including the possibilities for confusion that arise from the use of metaphor. The metaphor of a 'commentary machine' is suggested as a possible way forward and it is suggested that an appropriate linguistic analysis can in certain situations reduce perceived complexity

    The Partnership Paperchase: Structuring Partnership Agreements in Water and Sanitation in Low-income Communities

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    Tripartite partnerships between water utilities, local government and civil society are often seen as a good way to deliver services to informal urban communities and slums. However, while these 'partnerships' can be seen as benign relationships, they often fail because the incentives and interests of the partners are not well aligned. In this report, the authors argue that the development of robust documentation (in forms which consitute a 'contractual' agreement) can enhance the performance of such partnerships. Aspects of the partnership which should be included in such documentation include roles and responsibilities, financing, objectives and indicators of success and dispute-resolution mechanisms. The report provides practical guidance and examples of good practice to guide the reader through a process of developing such documentation

    The Partnership Paperchase: Structuring Partnership Agreements in Water and Sanitation in Low-income Communities

    No full text
    Tripartite partnerships between water utilities, local government and civil society are often seen as a good way to deliver services to informal urban communities and slums. However, while these 'partnerships' can be seen as benign relationships, they often fail because the incentives and interests of the partners are not well aligned. In this report, the authors argue that the development of robust documentation (in forms which consitute a 'contractual' agreement) can enhance the performance of such partnerships. Aspects of the partnership which should be included in such documentation include roles and responsibilities, financing, objectives and indicators of success and dispute-resolution mechanisms. The report provides practical guidance and examples of good practice to guide the reader through a process of developing such documentation
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