7 resultados para multi-agent incremental negotiation scheme

em Greenwich Academic Literature Archive - UK


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Belief revision is a well-research topic within AI. We argue that the new model of distributed belief revision as discussed here is suitable for general modelling of judicial decision making, along with extant approach as known from jury research. The new approach to belief revision is of general interest, whenever attitudes to information are to be simulated within a multi-agent environment with agents holding local beliefs yet by interaction with, and influencing, other agents who are deliberating collectively. In the approach proposed, it's the entire group of agents, not an external supervisor, who integrate the different opinions. This is achieved through an election mechanism, The principle of "priority to the incoming information" as known from AI models of belief revision are problematic, when applied to factfinding by a jury. The present approach incorporates a computable model for local belief revision, such that a principle of recoverability is adopted. By this principle, any previously held belief must belong to the current cognitive state if consistent with it. For the purposes of jury simulation such a model calls for refinement. Yet we claim, it constitutes a valid basis for an open system where other AI functionalities (or outer stiumuli) could attempt to handle other aspects of the deliberation which are more specifi to legal narrative, to argumentation in court, and then to the debate among the jurors.

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Belief revision is a well-researched topic within Artificial Intelligence (AI). We argue that the new model of belief revision as discussed here is suitable for general modelling of judicial decision making, along with the extant approach as known from jury research. The new approach to belief revision is of general interest, whenever attitudes to information are to be simulated within a multi-agent environment with agents holding local beliefs yet by interacting with, and influencing, other agents who are deliberating collectively. The principle of 'priority to the incoming information', as known from AI models of belief revision, is problematic when applied to factfinding by a jury. The present approach incorporates a computable model for local belief revision, such that a principle of recoverability is adopted. By this principle, any previously held belief must belong to the current cognitive state if consistent with it. For the purposes of jury simulation such a model calls for refinement. Yet, we claim, it constitutes a valid basis for an open system where other AI functionalities (or outer stimuli) could attempt to handle other aspects of the deliberation which are more specific to legal narratives, to argumentation in court, and then to the debate among the jurors.

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This paper presents work towards generic policy toolkit support for autonomic computing systems in which the policies themselves can be adapted dynamically and automatically. The work is motivated by three needs: the need for longer-term policy-based adaptation where the policy itself is dynamically adapted to continually maintain or improve its effectiveness despite changing environmental conditions; the need to enable non autonomics-expert practitioners to embed self-managing behaviours with low cost and risk; and the need for adaptive policy mechanisms that are easy to deploy into legacy code. A policy definition language is presented; designed to permit powerful expression of self-managing behaviours. The language is very flexible through the use of simple yet expressive syntax and semantics, and facilitates a very diverse policy behaviour space through both hierarchical and recursive uses of language elements. A prototype library implementation of the policy support mechanisms is described. The library reads and writes policies in well-formed XML script. The implementation extends the state of the art in policy-based autonomics through innovations which include support for multiple policy versions of a given policy type, multiple configuration templates, and meta-policies to dynamically select between policy instances and templates. Most significantly, the scheme supports hot-swapping between policy instances. To illustrate the feasibility and generalised applicability of these tools, two dissimilar example deployment scenarios are examined. The first is taken from an exploratory implementation of self-managing parallel processing, and is used to demonstrate the simple and efficient use of the tools. The second example demonstrates more-advanced functionality, in the context of an envisioned multi-policy stock trading scheme which is sensitive to environmental volatility

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This paper presents primary data based on research carried out as part of a large World Bank project. Results from our survey show that water pollution in Dhaka watershed has reached alarming levels and is posing significant threats to health and economic activity, particularly among the poor and vulnerable. Rice productivity in the watershed area, for example, has declined by 40% in recent years and vegetable cultivation in the riverbeds has been severely damaged. We also found significant correlation between water pollution and diseases such as jaundice, diarrhoea and skin problems. It was reported that the cost of treatment of skin diseases for one episode could be as high as 29% of the weekly earnings of poor households. Given the magnitude of the contamination problem, a multi-agent stakeholder approach was necessary to analyse the institutional and economic constraints that would need to be addressed in order to improve environmental management. This approach, in turn, enabled core strategies to be developed. The strategies were better understood around three types of actors in industrial pollution, i.e. (1) principal actors, who contribute directly to industrial pollution; (2) stakeholders, who exacerbate the situation by inaction; and (3) the potential actors in mitigation of water contamination. Within a carrot-and-stick framework, nine strategies leading to the strengthening of environmental management were explored. They aim at improving governance and transparency within public agencies and private industry through the setting up of incentive structures to advance compliance and enforcement of environmental standards. Civil society and the population at large are, on the other hand, encouraged to contribute actively to the mitigation of water pollution by improving the management of environmental information and by raising public awareness.

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The objective of this work is to present a new scheme for temperature-solute coupling in a solidification model, where the temperature and concentration fields simultaneously satisfy the macro-scale transport equations and, in the mushy region, meet the constraints imposed by the thermodynamics and the local scale processes. A step-by-step explanation of the macrosegregation algorithm, implemented in the finite volume unstructured mesh multi-physics modelling code PHYSICA, is initially presented and then the proposed scheme is validated against experimental results obtained by Krane for binary and a ternary alloys.

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A numerical scheme for coupling temperature and concentration fields in a general solidification model is presented. A key feature of this scheme is an explicit time stepping used in solving the governing thermal and solute conservation equations. This explicit approach results in a local point-by-point coupling scheme for the temperature and concentration and avoids the multi-level iteration required by implicit time stepping schemes. The proposed scheme is validated by predicting the concentration field in a benchmark solidification problem. Results compare well with an available similarity solution. The simplicity of the proposed explicit scheme allows for the incorporation of complex microscale models into a general solidification model. This is demonstrated by investigating the role of dendrite coarsening on the concentration field in the solidification benchmark problem.

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Purpose: The purpose of this paper is to investigate the impact of different agency practice on agency fees, business efficiency, and housing market liquidity. Design/methodology/approach: The paper studies the effect of sole and multiple agency practices on estate agent efficiency, housing market liquidity, and commission fee levels. The analysis uses the survey data from 2000 to 2006 to investigate the different agency practices across England and Wales and their effect on estate agency business efficiency, housing market liquidity, selling price, and fee levels. Findings: The empirical analysis confirms that agency practice has a locality bias, that is, some regions are more likely to adopt sole agency practice than other regions. The estate agents with a sole agency practice charge a lower agency fee, help clients to achieve better selling price and are more efficient; whereas multiple agency practice facilitates liquidity in the housing market, but experiences higher fall-through rate. Research limitations/implications: The research focuses on estate agent rather than consumers due to the limitation of the data based on a research project concerning transaction costs designed prior to this analysis. Originality/value: There is little other research that investigates the residential estate agency practice and its impact on housing market in the past three decades in England and Wales. The findings are a useful guide for practitioners to better understand the issues associated with different agency practices and should enhance business efficiency and performance.