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

Efficient performative actions for e-commerce agents

The foundational features of multi-agent systems are communication and interaction with other agents. To achieve these features, agents have to transfer messages in the predefined format and semantics. The communication among these agents takes place with the help of ACL (Agent Communication Language). ACL is a predefined language for communication among agents that has been standardised by the FIPA (Foundation for Intelligent Physical Agent). FIPA-ACL defines different performatives for communication among the agents. These performatives are generic, and it becomes computationally expensive to use them for a specific domain like e-commerce. These performatives do not define the exact meaning of communication for any specific domain like e-commerce. In the present research, we introduced new performatives specifically for e-commerce domain. Our designed performatives are based on FIPA-ACL so that they can still support communication within diverse agent platforms. The proposed performatives are helpful in modelling e-commerce negotiation protocol applications using the paradigm of multi-agent systems for efficient communication. For exact semantic interpretation of the proposed performatives, we also performed formal modelling of these performatives using BNF. The primary objective of our research was to provide the negotiation facility to agents, working in an e-commerce domain, in a succinct way to reduce the number of negotiation messages, time consumption and network overhead on the platform. We used an e-commerce based bidding case study among agents to demonstrate the efficiency of our approach. The results showed that there was a lot of reduction in total time required for the bidding process

Building a Semantic Tendering System

In the new B2B e-commerce arena, applications such as auctions and data exchange are growing rapidly. However, Web content is currently designed for human consumption rather than computer manipulation. This limits the possibility of Web automation. Fortunately, the new development of the Semantic Web that allows Web pages to provide information not only in terms of their content, but also in terms of the properties of that content, can be used for automation. Electronic tendering systems are among the successfully commercial systems that can tremendously benefit from the availability of Semantic Web. This study proposes an e-tendering system that uses the Semantic Web to investigate the automatic negotiation process. The system is built in a P2P environment to simulate a two-player negotiation. It is found that the ontology of semantic information can be used to locate qualified suppliers and precede negotiation. The bargaining power of each party is then determined by the relative magnitude of the negotiators’ respective costs of haggling and the utility that varies with the degree of risk preference. Our experiments showed that applying automatic negotiation strategies to e-tendering system in semantic web can reflect the risk preference of the participants

Service-oriented architecture for ontologies supporting multi-agent system negotiations in virtual enterprise

This paper offers a service-oriented architecture (SOA) for ontology-based multi-agent system (MAS) negotiations in the context of virtual enterprises (VEs). The objective of this paper is fourfold. First, it is to design a SOA which utilizes ontology and MAS to provide a distributed and interoperable environment for automated negotiations in VE. In this architecture, individual ontologies for both the VE initiator and its potential partners are constructed to describe and store resources and service knowledge. Second, a series of semantic ontology matching methods are developed to reach agents' interoperability during the negotiation process. Third, correspondence-based extended contract net protocol is presented, which provides basic guidelines for agents' reaching mutual understandings and service negotiation. Last, a fuzzy set theory based knowledge reuse approach is proposed to evaluate the current negotiation behaviors of the VE partners. A walkthrough example is presented to illustrate the methodologies and system architecture proposed in this paper. © 2010 The Author(s).published_or_final_versionSpringer Open Choice, 21 Feb 201

On the Use of Optimization Techniques for Strategy Definition in Multi Issue Negotiations

Στην παρούσα διπλωματική εργασία αναλύεται το πρόβλημα της λήψης απόφασης σε συστήματα αυτόματων διαπραγματεύσεων. Σκοπός είναι να σχεδιαστεί ένας αποδοτικός αλγόριθμος βάσει του οποίου οι πράκτορες λογισμικού θα δρουν σε ένα σενάριο ταυτόχρονων διαπραγματεύσεων.Οι πράκτορες δεν έχουν καμία πληροφόρηση για τα χαρακτηριστικά των αντιπάλων.Οι διαπραγματεύσεις πραγματοποιούνται με απώτερο στόχο την ανταλλαγή προϊόντων μεταξύ αγοραστών και πωλητών με συγκεκριμένα ανταλλάγματα. Κάθε προϊόν χαρακτηρίζεται από μια ομάδα χαρακτηριστικών. Για παράδειγμα, ένα προϊόν μπορεί να χαρακτηριζεται από την τιμή, από το χρόνο παράδοσης, κλπ. Κάθε αγοραστής αντιστοιχίζεται στις αυτόματες διαπραγματεύσεις με έναν αριθμό πωλητών. Προτείνουμε αλγόριθμους που προσπαθούν να επιλύσουν το πρόβλημα προσέγγισης αβεβαιότητας με τελικό σκοπό τη μεγιστοποίηση της ανταμοιβής των χρηστών. Η ανταμοιβή υπολογίζεται ως το άθροισμα με τα αντίστοιχα βάρη των χαρακτηριστικών. Εστιάζουμε στην πλευρά του αγοραστή και ορίζουμε μεθοδους για τον υπολογισμό των βαρών που επηρεάζουν τη χρησιμότητα του χρήστη. Πιο συγκεκριμένα, προτείνουμε μεθόδους για την αλλαγή της στρατηγικής του αγοραστή με στόχο να προσεγγίσουμε την καλύτερη συμφωνία. Ακόμα, χρησιμοποείται ο αλγόριθμος της θεωρία του σμήνους (Particle Swarm Optimization Algorithm) ώστε μέσω της κίνησης στο Ν-διαστατο χώρο να συγκλίνουν οι πράκτορες λογισμικού στη βέλτιστη συμφωνία. Παρουσιάζεται, τέλος, ένας αριθμός από πειράματα για τις προτεινόμενες μεθόδους για να αξιολογηθεί η απόδοσή τους και να συγκριθούν τα αποτελέσματα με τη σχετική βιβλιογραφία. In this thesis, we deal with the problem of decision making in automated negotiations. We consider the case where software agents undertake the responsibility of representing their owners in such negotiations. The final aim is to provide an efficient algorithm in which software agents will act in a scenario of concurrent negotiations. Agents have no knowledge on the opponents’ characteristics. Negotiations are held for the exchange of products between buyers and sellers with specific returns. Each product is characterized by a set of issues. For example, a product could be characterized by its price, delivery time, and so on. The buyer is involved in concurrent negotiations with a number of sellers. We propose algorithms that try to solve the problem of handling the uncertainty with the final aim of maximizing the entities rewards. The reward is calculated as a weighted sum of the discussed issue values. We focus on the buyer side and define specific methodologies for defining the weights that affect the utility of the buyer. Moreover, we propose a methodology for changing the strategy of the buyer in order to reach the optimal agreement. We are based on the widely known Particle Swarm Optimization (PSO) algorithm that is implemented by software agents’ movements in N-dimensional space to reach the optimal solution. We present a number of experiments for the proposed methodologies that show their performance and we compare our results with results found in the literature