2,782 research outputs found
KEMNAD: A Knowledge Engineering Methodology for Negotiating Agent Development
Automated negotiation is widely applied in various domains. However, the development of such systems is a complex knowledge and software engineering task. So, a methodology there will be helpful. Unfortunately, none of existing methodologies can offer sufficient, detailed support for such system development. To remove this limitation, this paper develops a new methodology made up of: (1) a generic framework (architectural pattern) for the main task, and (2) a library of modular and reusable design pattern (templates) of subtasks. Thus, it is much easier to build a negotiating agent by assembling these standardised components rather than reinventing the wheel each time. Moreover, since these patterns are identified from a wide variety of existing negotiating agents(especially high impact ones), they can also improve the quality of the final systems developed. In addition, our methodology reveals what types of domain knowledge need to be input into the negotiating agents. This in turn provides a basis for developing techniques to acquire the domain knowledge from human users. This is important because negotiation agents act faithfully on the behalf of their human users and thus the relevant domain knowledge must be acquired from the human users. Finally, our methodology is validated with one high impact system
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
Increasing negotiation performance at the edge of the network
Automated negotiation has been used in a variety of distributed settings,
such as privacy in the Internet of Things (IoT) devices and power distribution
in Smart Grids. The most common protocol under which these agents negotiate is
the Alternating Offers Protocol (AOP). Under this protocol, agents cannot
express any additional information to each other besides a counter offer. This
can lead to unnecessarily long negotiations when, for example, negotiations are
impossible, risking to waste bandwidth that is a precious resource at the edge
of the network. While alternative protocols exist which alleviate this problem,
these solutions are too complex for low power devices, such as IoT sensors
operating at the edge of the network. To improve this bottleneck, we introduce
an extension to AOP called Alternating Constrained Offers Protocol (ACOP), in
which agents can also express constraints to each other. This allows agents to
both search the possibility space more efficiently and recognise impossible
situations sooner. We empirically show that agents using ACOP can significantly
reduce the number of messages a negotiation takes, independently of the
strategy agents choose. In particular, we show our method significantly reduces
the number of messages when an agreement is not possible. Furthermore, when an
agreement is possible it reaches this agreement sooner with no negative effect
on the utility.Comment: Accepted for presentation at The 7th International Conference on
Agreement Technologies (AT 2020
Integration of decision support systems to improve decision support performance
Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes
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