Automated Purchase Negotiations in a Dynamic Electronic Marketplace

Nowadays, there is a surge of B2C and B2B e-commerce operated\ud on the Internet. However, many of these systems are often nothing\ud more than electronic product or service catalogues. Against this background,\ud it is argued that new generation systems based on automatic\ud negotiation will emerge. This paper covers a particular kind of automatic\ud negotiation systems, where a number of participants in a mobile\ud dynamic electronic marketplace automatically negotiate the purchase of\ud products or services, by means of multiple automated one-to-one bargainings.\ud In a dynamic e-marketplace, the number of buyers and sellers\ud and their preferences may change over time. By mobile we mean that\ud buyers in a commercial area may initiate simultaneous negotiations with\ud several sellers using portable devices like cell phones, laptops or personal\ud digital assistants, so these negotiations do not require participants to be\ud colocated in space. We will show how an expressive approach to fuzzy\ud constraint based agent purchase negotiations in competitive trading environments,\ud is ideally suited to work on these kind of e-marketplaces. An\ud example of mobile e-marketplace, and a comparison between an expressive\ud and an inexpressive approach will be presented to show the efficiency\ud of the proposed solution

Strategies for offer generation and relaxation in fuzzy constraint-based negotiation models

Ministerio de Educación y Cienci

A Region-Based Multi-Issue Negotiation Protocol For Non-Monotonic Utility Spaces

Ministerio de Educación y Cienci

Addressing stability issues in mediated complex contract negotiations for constraint-based, non-monotonic utility spaces

Negotiating contracts with multiple interdependent issues may yield non- monotonic, highly uncorrelated preference spaces for the participating agents. These scenarios are specially challenging because the complexity of the agents’ utility functions makes traditional negotiation mechanisms not applicable. There is a number of recent research lines addressing complex negotiations in uncorrelated utility spaces. However, most of them focus on overcoming the problems imposed by the complexity of the scenario, without analyzing the potential consequences of the strategic behavior of the negotiating agents in the models they propose. Analyzing the dynamics of the negotiation process when agents with different strategies interact is necessary to apply these models to real, competitive environments. Specially problematic are high price of anarchy situations, which imply that individual rationality drives the agents towards strategies which yield low individual and social welfares. In scenarios involving highly uncorrelated utility spaces, “low social welfare” usually means that the negotiations fail, and therefore high price of anarchy situations should be avoided in the negotiation mechanisms. In our previous work, we proposed an auction-based negotiation model designed for negotiations about complex contracts when highly uncorrelated, constraint-based utility spaces are involved. This paper performs a strategy analysis of this model, revealing that the approach raises stability concerns, leading to situations with a high (or even infinite) price of anarchy. In addition, a set of techniques to solve this problem are proposed, and an experimental evaluation is performed to validate the adequacy of the proposed approaches to improve the strategic stability of the negotiation process. Finally, incentive-compatibility of the model is studied.Spain. Ministerio de Educación y Ciencia (grant TIN2008-06739-C04-04

Dynamic resource allocation in fuzzy coalitions : a game theoretic model

We introduce an efficient and dynamic resource allocation mechanism within the framework of a cooperative game with fuzzy coalitions. A fuzzy coalition in a resource allocation problem can be so defined that membership grades of the players in it, are proportional to the fractions of their total resources. We call any distribution of the resources possessed by the players, among a prescribed number of coalitions, a fuzzy coalition structure and every membership grade (equivalently fraction of the total resource), a resource investment. It is shown that this resource investment is influenced by satisfaction of the players in regards to better performance under a cooperative setup. Our model is based on the real life situations, where possibly one or more players compromise on their resource investments in order to help forming a coalition

Dynamic resource allocation in fuzzy coalitions : a game theoretic model

We introduce an efficient and dynamic resource allocation mechanism within the framework of a cooperative game with fuzzy coalitions. A fuzzy coalition in a resource allocation problem can be so defined that membership grades of the players in it, are proportional to the fractions of their total resources. We call any distribution of the resources possessed by the players, among a prescribed number of coalitions, a fuzzy coalition structure and every membership grade (equivalently fraction of the total resource), a resource investment. It is shown that this resource investment is influenced by satisfaction of the players in regards to better performance under a cooperative setup. Our model is based on the real life situations, where possibly one or more players compromise on their resource investments in order to help forming a coalition

Modeling the Decision Process of a Joint Task Force Commander

The U.S. military uses modeling and simulation as a tool to help meet its warfighting needs. A key element within military simulations is the ability to accurately represent human behavior. This is especially true in a simulation\u27s ability to emulate realistic military decisions. However, current decision models fail to provide the variability and flexibility that human decision makers exhibit. Further, most decision models are focused on tactical decisions and ignore the decision process of senior military commanders at the operational level of warfare. In an effort to develop a better decision model that would mimic the decision process of a senior military commander, this research sought to identify an underlying cognitive process and computational techniques that could adequately implement it. Recognition-Primed Decision making (RPD) was identified as one such model that characterized this process. Multiagent system simulation was identified as a computational system that could mimic the cognitive process identified by RPD. The result was a model of RPD called RPDAgent. Using an operational military decision scenario, decisions produced by RPDAgent were compared against decisions made by military officers. It was found that RPDAgent produced decisions that were equivalent to its human counterparts. RPDAgent\u27s decisions were not optimum decisions, but decisions that reflected the variability inherent in those made by humans in an operational military environment

Implementation of a rewards based negotiation module for an e commerce platform

Information and Communication Technologies (ICTs) have been widely deployed in developmental programs and this has lead to the creation of a new field – ICT for Development (ICT4D). Within the context of ICT4D, various e-services are being developed, including e-Commerce, e-Government, e-Health and e-Judiciary. ICT4D projects allow Small, Medium and Micro Enterprises (SMMEs) in rural areas to increase sales and gain a market share in the global market. However, many of these ICT4D projects do not succeed, because they fail to bring enough financial value to SMMEs due to the form they currently have. An obvious example is e-Commerce, which should be a source of revenue for business organizations, but most often is not. This thesis presents the design and implementation of a rewarding and negotiation application for a shopping portal to improve the marketing of products for rural entrepreneurs. The shopping portal has been set up for the Dwesa community, a marginalized area in the Eastern Cape province of South Africa. The proposed system, called the Dwesa Rewarding Program (DRP) enables customers buying online to get points for some of the activities carried out on the shopping portal. It also allows customers to negotiate and make offers whilst purchasing and get rewarded for buying online. The novelty of the system is in its flexibility and adaptability. One achievement of this system is the establishment of negotiation rules which allows fairness in rewarding customers. This should in turn lead to increased sales on the e-Commerce platform in marginalized areas and subsequently increased effectiveness of ICT4D for socio-economic developmen

Debugging multi-agent systems with design documents

Debugging multi-agent systems, which are concurrent, distributed, and consist of complex components is difficult, yet crucial. The development of these complex systems is supported by agent-oriented software engineering methodologies which utilise agents as the central design metaphor. The systems that are developed are inherently complex since the components of these systems may interact in flexible and sophisticated ways and traditional debugging techniques are not appropriate. Despite this, very little effort has been applied to developing appropriate debugging tools and techniques. Debugging multi-agent systems without good debugging tools is highly impractical and without suitable debugging support developing and maintaining multi-agent systems will be more difficult than it need be. In this thesis we propose that the debugging process can be supported by following an agent-oriented design methodology, and then using the developed design artifacts in the debugging phase. We propose a domain independent debugging framework which comprises the developed processes and components that are necessary in using design artifacts as debugging artifacts. Our approach is to take a non-formal design artifact, such as an AUML protocol design, and encode it in a machine interpretable manner such that the design can be used as a model of correct system behaviour. These models are used by a run-time debugging system to compare observed behaviour against specified behaviour. We provide details for transforming two design artifact types into equivalent debugging artifacts and show how these can be used to detect bugs. During a debugging episode in which a bug has been identified our debugging approach can provide detailed information about the possible reason for the bug occurring. To determine if this information was useful in helping to debug programs we undertook a thorough empirical study and identified that use of the debugging tool translated to an improvement in debugging performance. We conclude that the debugging techniques developed in this thesis provide effective debugging support for multi-agent systems and by having an extensible framework new design artifacts can be explored and as translations are developed they can be added to the debugging system

Contribución a la negociación automática en espacios de utilidad complejos

Premio Extraordinario de Doctorado 2012Podemos entender la negociación como una interacción entre varias partes que intentan alcanzar un acuerdo en relación a una serie de atributos que les suponen un conflicto de intereses. Así definida, la negociación está presente en numerosos aspectos de la vida cotidiana, desde las relaciones personales a la economía o la política internacional. Algunos escenarios de negociación pueden ser total o parcialmente automatizados, beneficiándose así de las ventajas en cuanto a eficiencia del empleo de técnicas de inteligencia artificial. Entre los problemas que ya se han abordado con éxito en la literatura haciendo uso de negociación automática entre agentes podemos destacar diferentes escenarios de negociación en comercio electrónico y problemas de reparto de recursos o tareas, como por ejemplo cadenas de producción o reparto de carga computacional en procesos informáticos. La automatización de los procesos de negociación permite no sólo replicar la toma de decisiones humana en escenarios de negociación tradicionales, sino también abordar problemas en los que la negociación con humanos no es viable, ya sea por la complejidad del escenario o por las limitaciones temporales del proceso de negociación. Dentro de este ámbito, existe un interés creciente por el estudio de escenarios de negociación complejos, como pueden ser las negociaciones de contratos jurídicos o los acuerdos de requisitos entre proveedores y clientes. En este tipo de escenarios, son frecuentes las negociaciones de múltiples atributos interdependientes. La complejidad inherente a este tipo de problemas de negociación sugiere la automatización total o parcial del proceso, especialmente cuando existen restricciones temporales severas sobre la duración de la negociación. Sin embargo, la dependencia entre atributos genera espacios de utilidad no lineales, haciendo que los mecanismos clásicos de negociación automática no sean aplicables. Incluso mecanismos específicamente diseñados para escenarios no lineales pueden fallar si la complejidad del espacio de utilidades aumenta considerablemente. Existe, por tanto, la necesidad de diseñar mecanismos que permitan negociar de forma efectiva y eficaz en escenarios que impliquen espacios de utilidad de elevada complejidad. Esta tesis aborda el problema de la negociación automática multilateral en espacios de utilidad complejos, tratando de dar respuesta a esta necesidad. Para ello se propone un modelo de negociación especialmente diseñado para este tipo de escenarios. El modelo comprende la representación de las preferencias de los agentes, la especificación del protocolo de interacción que gobierna la negociación, y el diseño de estrategias heurísticas para la toma de decisiones de los agentes. Para las preferencias de los agentes, se opta por funciones de utilidad basadas en restricciones ponderadas, y se presenta un generador de preferencias que permite diseñar, a partir de un conjunto de parámetros, escenarios de complejidad ajustable, tanto en lo referente a la complejidad de los espacios de preferencias individuales de los agentes como en lo referente a la correlación mutua de las funciones de utilidad de los diferentes agentes. Para el proceso de negociación, este trabajo parte de la hipótesis de que, en escenarios en los que los espacios de utilidad de los agentes son complejos, la dificultad de la consecución de acuerdos mutuamente aceptables puede paliarse buscando un equilibrio adecuado entre los objetivos individuales de maximización de la utilidad de cada agente, y el objetivo social de la consecución del acuerdo. Teniendo esto en cuenta, se propone un protocolo de interacción expresivo e iterativo basado en subastas, que permite a los agentes refinar sus propuestas en cada iteración sirviéndose de la capacidad expresiva que proporcionan las técnicas de argumentación. Finalmente, se diseña un conjunto de estrategias para la toma de decisiones de los agentes, orientadas a equilibrar el beneficio obtenido y la probabilidad de acuerdo en función de la actitud hacia el riesgo de cada agente. Una vez formulada la propuesta, se ha realizado una exhaustiva evaluación experimental orientada a determinar la contribución a la negociación de los mecanismos propuestos en términos de efectividad y eficiencia. Los experimentos realizados han confirmado nuestra hipótesis de trabajo y la adecuación de nuestra propuesta basada en el equilibrio entre utilidad y probabilidad de acuerdo y la capacidad expresiva de los agentes, y nos han permitido extraer importantes conclusiones en el ámbito de investigación de los sistemas de negociación automática multilateral multiatributo para espacios de utilidad complejos