This paper develops a fuzzy constraint based model for bilateral multi-issue negotiation in trading environments. In particular, we are concerned with the principled negotiation approach in which agents seek to strike a fair deal for both parties, but which, nevertheless, maximises their own payoff. Thus, there are elements of both competition and cooperation in the negotiation (hence semicompetitive environments). One of the key intuitions of the approach is that there is often more than one option that can satisfy the interests of both parties. So, if the opponent cannot accept an offer then the proponent should endeavour to find an alternative that is equally acceptable to it, but more acceptable to the opponent. That is, the agent should make a trade-off. Only if such a trade-off is not possible should the agent make a concession. Against this background, our model ensures the agents reach a deal that is fair (Pareto-optimal) for both parties if such a solution exists. Moreover, this is achieved by minimising the amount of private information that is revealed. The model uses prioritised fuzzy constraints to represent trade-offs between the different possible values of the negotiation issues and to indicate how concessions should be made when they are necessary. Also by using constraints to express negotiation proposals, the model can cover the negotiation space more efficiently since each exchange covers a region rather than a single point (which is what most existing models deal with). In addition, by incorporating the notion of a reward into our negotiation model, the agents can sometimes reach agreements that would not otherwise be possible.

About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractThe recent global outbreak of Severe Acute Respiratory Syndrome has aroused public concern on environmental health and hygiene. Develops a practical assessment scheme for assessing the health and hygiene performance of apartment buildings in Hong Kong. The scheme involves assessing a hierarchy of building factors that have a bearing on environmental qualities, and thus occupants' health. Proposes an index method to integrate the assessment outcomes into a simple and user-friendly performance indicator for public consumption. The index can inform the public of the health and hygiene risk of different buildings and facilitate building owners, developers, and government bodies to make more informed and socially responsible decisions on environmental health and hygiene improvement. Although the assessment scheme is tailored for the institutional and cultural settings of Hong Kong, the assessment framework for the development of the scheme is also applicable to other cities.

Abstract-Collaborative filtering (CF) is an important and popular technology for recommender systems. However, current CF methods suffer from such problems as data sparsity, recommendation inaccuracy, and big-error in predictions. In this paper, we borrow ideas of object typicality from cognitive psychology and propose a novel typicality-based collaborative filtering recommendation method named TyCo. A distinct feature of typicality-based CF is that it finds "neighbors" of users based on user typicality degrees in user groups (instead of the corated items of users, or common users of items, as in traditional CF). To the best of our knowledge, there has been no prior work on investigating CF recommendation by combining object typicality. TyCo outperforms many CF recommendation methods on recommendation accuracy (in terms of MAE) with an improvement of at least 6.35 percent in Movielens data set, especially with sparse training data (9.89 percent improvement on MAE) and has lower time cost than other CF methods. Further, it can obtain more accurate predictions with less number of big-error predictions.

A high-density built environment poses challenges to the idea of sustainable development in respect of health (e.g. SARS outbreak) and safety (e.g. fire and structural problems). To examine the seriousness of the high-density problem, this study aims to survey the health and safety performance of apartment buildings in a densely populated city, Hong Kong, using a simplified assessment scheme. An assessment scheme based on a hierarchy of building performance indicators concerning the quality of: (a) architectural design, (b) building services design, (c) the surrounding environment, (d) operations and maintenance, and (e) management approaches was developed. One hundred forty (140) apartment buildings were surveyed and assessed through site inspections, desk searches, and interviews. A performance analysis was conducted to examine and compare the overall health and safety performance of the buildings. We found that there were considerable variations in health and safety conditions across buildings, even though they are located within a single district. Most of the variations in building health and safety conditions were attributed to differences in building management systems rather than building design. Enhancing strategic management approaches (e.g. a better delineation of owners' rights and duties) appears to be the most critical factor that underperformers should consider in order to improve their buildings.

This paper identiÿes a generic axiom framework for prioritised fuzzy constraint satisfaction problems (PFCSPs), and proposes methods to instantiate it (i.e., to construct speciÿc schemes which obey the generic axiom framework). In particular, we give ÿve methods to construct the priority operators that are used for calculating the local satisfaction degree of a prioritised fuzzy constraint, and identify priority T-norm operators that can be used for calculating the global satisfaction degree of a prioritised fuzzy constraint problem. Moreover, a number of numerical examples and real examples are used to validate our system, and thus we further obtain some insights into our system. In addition, we explore the relationship between weight schemes and prioritised FCSP schemes, and reveal that the weighted FCSP schemes are the dual of prioritised FCSP schemes, which can, correspondingly, be called posterioritised FCSP schemes.