Automated Bilateral Bargaining about Multiple Attributes in a One­ to ­Many Setting

Negotiations are an important way of reaching agreements between selfish autonomous agents. In this paper we focus on one-to-many bargaining within the context of agent-mediated electronic commerce. We consider an approach where a seller agent negotiates over multiple interdependent attributes with many buyer agents in a bilateral fashion. In this setting, "fairness", which corresponds to the notion of envy-freeness in auctions, may be an important business constraint. For the case of virtually unlimited supply (such as information goods), we present a number of one-to-many bargaining strategies for the seller agent, which take into account the fairness constraint, and consider multiple attributes simultaneously. We compare the performance of the bargaining strategies using an evolutionary simulation, especially for the case of impatient buyers. Several of the developed strategies are able to extract almost all the surplus; they utilize the fact that the setting is one-to-many, even though bargaining is bilateral

Negotiating over Bundles and Prices Using Aggregate Knowledge

Combining two or more items and selling them as one good, a practice called bundling, can be a very effective strategy for reducing the costs of producing, marketing, and selling goods. In this paper, we consider a form of multi-issue negotiation where a shop negotiates both the contents and the price of bundles of goods with his customers. We present some key insights about, as well as a technique for, locating mutually beneficial alternatives to the bundle currently under negotiation. The essence of our approach lies in combining historical sales data, condensed into aggregate knowledge, with current data about the ongoing negotiation process, to exploit these insights. In particular, when negotiating a given bundle of goods with a customer, the shop analyzes the sequence of the customer's offers to determine the progress in the negotiation process. In addition, it uses aggregate knowledge concerning customers' valuations of goods in general. We show how the shop can use these two sources of data to locate promising alternatives to the current bundle. When the current negotiation's progress slows down, the shop may suggest the most promising of those alternatives and, depending on the customer's response, continue negotiating about the alternative bundle, or propose another alternative. Extensive computer simulation experiments show that our approach increases the speed with which deals are reached, as well as the number and quality of the deals reached, as compared to a benchmark. In addition, we show that the performance of our system is robust to a variety of changes in the negotiation strategies employed by the customers.Comment: 15 pages, 7 eps figures, Springer llncs documentclass. Extended version of the paper published in "E-Commerce and Web Technologies," Kurt Bauknecht, Martin Bichler and Birgit Pr\"{o}ll (eds.). Springer Lecture Notes in Computer Science, Volume 3182, Berlin: Springer, p. 218--22

Online Learning of Aggregate Knowledge about Non-linear Preferences Applied to Negotiating Prices and Bundles

In this paper, we consider a form of multi-issue negotiation where a shop negotiates both the contents and the price of bundles of goods with his customers. We present some key insights about, as well as a procedure for, locating mutually beneficial alternatives to the bundle currently under negotiation. The essence of our approach lies in combining aggregate (anonymous) knowledge of customer preferences with current data about the ongoing negotiation process. The developed procedure either works with already obtained aggregate knowledge or, in the absence of such knowledge, learns the relevant information online. We conduct computer experiments with simulated customers that have_nonlinear_ preferences. We show how, for various types of customers, with distinct negotiation heuristics, our procedure (with and without the necessary aggregate knowledge) increases the speed with which deals are reached, as well as the number and the Pareto efficiency of the deals reached compared to a benchmark.Comment: 10 pages, 5 eps figures, ACM Proceedings documentclass, Published in "Proc. 6th Int'l Conf. on Electronic Commerce ICEC04, Delft, The Netherlands," M. Janssen, H. Sol, R. Wagenaar (eds.). ACM Pres

Efficient Methods for Automated Multi-Issue Negotiation: Negotiating over a Two-Part Tariff

In this article, we consider the novel approach of a seller and customer negotiating bilaterally about a two-part tariff, using autonomous software agents. An advantage of this approach is that win-win opportunities can be generated while keeping the problem of preference elicitation as simple as possible. We develop bargaining strategies that software agents can use to conduct the actual bilateral negotiation on behalf of their owners. We present a decomposition of bargaining strategies into concession strategies and Pareto-efficient-search methods: Concession and Pareto-search strategies focus on the conceding and win-win aspect of bargaining, respectively. An important technical contribution of this article lies in the development of two Pareto-search methods. Computer experiments show, for various concession strategies, that the respective use of these two Pareto-search methods by the two negotiators results in very efficient bargaining outcomes while negotiators concede the amount specified by their concession strategy

Examining How Physical Activity Patterns Relate To Psychosocial Health Among Children (Ages 4 6 Years) In Canada: National Longitudinal Survey Of Children And Youth (NLSCY) 1996-2008.

Background: Declining rates of total physical activity (PA) among children are disconcerting; however, research on PA and sport participation including potential benefits for psychosocial development is still in the early stages. Objectives: i) To estimate the prevalence and predictors of organized physical activity (OPA) participation among 46-year-olds across Canada from 1996 to 2008, and ii) to evaluate psychosocial outcomes associated with sport/OPA and unorganized physical activity (UPA). Methods: Data from 46-year-olds in the 19962008 National Longitudinal Survey of Children and Youth (weighted n= ~5 572 000) were pooled and cross-classified with PA types (inactivity, OPA, UPA, and combined PA). Results: Over half of 46-year-olds (53.4%) were engaged in OPA. Better psychosocial development was generally seen amongst frequent OPA groups, 5- and 6-year-olds, and those with a higher household income. Conclusion: Parental involvement and socioeconomic advantage are central to engagement in (and psychosocial benefit from) OPA participation

Upshot of virulence markers and effects of temperature and pH on haemolytic bacteria in South-west Nigeria

Background: Virulence is the extent of pathogenicity displayed by majority of pathogens and yardstick that efficiently distinguishes pathogenic and non-pathogenic organisms.Effects of pH, temperature and incubation period were studied on capsule-positive bacteria isolated from Onyearugbulem stream, Akure. Methods: Water samples from Onyearugbulem stream in Akure was collected in sterile 500ml sample bottles. Water samples obtained from the stream were subjected to microbiological analysis. Implicated bacteria were tested for haemolysis and virulence determination via blood agar (5% v/v) and for the presence of capsule using India ink. ß-haemolytic bacteria were subjected to different temperature (15 °C – 60 °C) and pH (6.0 – 9.0) ranges. pH conditions were achieved by the addition of 0.01M NaOH and 0.01M HCl to media  before sterilization. The zones of clearance (mm) were measured at 24 h, 48 h and 72 h. Results: Proteus penneri showed the highest haemolytic activity (56 mm) at 28 °Cafter a duration of 72 h. Bacillus cereus showed the highest haemolytic activity (52 mm) at pH 8.5, after 72 h Dye degradation was optimum at 10 to 12 h at 37 °C which showed the haemolytic bacterial organisms were capsule-positive. Conclusion: The findings in this study revealed that bacteria present in Onyearugbulem stream contained virulent factors with highest activity at ambient temperature (28 °C) which indicate the poor quality of the stream and thereby constitute serious health threat to man and animal

Web based fingerprint roll call attendance management system

Managing people and keeping adequate record of the attendance for most of the tertiary institutions are difficult task. Moreover, the manual taking of attendance adds to the difficulty of this task because it is strenuous, time intensive and can easily be falsified. Meanwhile, With the advent of new technology, a new world of authentication and security has been created via biometrics. This work aims at improving Covenant Universities paper-based attendance by using biometrics, specifically fingerprint technology. It is a web application that works with a fingerprint reader from which the features of the student’s fingerprint are extracted during enrolment. This is also needed during the authentication phase which occurs during the roll call attendance in the halls of residence. It is implemented using PHP and MySQL

Bundling and pricing for information brokerage: customer satisfaction as a means to profit optimization

Traditionally, the study of on-line dynamic pricing and bundling strategies for information goods is motivated by the value-extracting or profit-generating potential of these strategies. In this paper we discuss the relatively overlooked potential of these strategies to on-line learn more about customers' preferences. Based on this enhanced customer knowledge an information broker can-- by tailoring the brokerage services more to the demand of the various customer groups-- persuade customers to engage in repeated transactions (i.e., generate customer lock-in). To illustrate the discussion, we show by means of a basic consumer model how, with the use of on-line dynamic bundling and pricing algorithms, customer lock-in can occur. The lock-in occurs because the algorithms can both find appropriate prices and (from the customers' perspective) the most interesting bundles. In the conducted computer experiments we use an advanced genetic algorithm with a niching method to learn the most interesting bundles efficiently and effectively