Unit:
Κατεύθυνση / ειδίκευση Διαχείριση Πληροφορίας και Δεδομένων (ΔΕΔ)Library of the School of Science
Dissertation committee:
Μαρτάκος Δρακούλης Αν. Καθηγητής ΕΚΠΑ (επιβλέπων), Χαλάτσης Κωνσταντίνος Ομ. Καθηγητής ΕΚΠΑ, Γεωργιάδης Παναγιώτης Καθηγητής ΕΚΠΑ
Original Title:
E-Negotiations for trading commodities and services: predictive strategies = Ηλεκτρονικές διαπραγματεύσεις για την προμήθεια αγαθών και υπηρεσιών: στρατηγικές πρόβλεψης
Summary:
This thesis takes into account the advances in the field of electronic
bi-lateral negotiations, adopting state-of-the-art protocols and strategies
that characterize the behavior of each party. The research objective is the
application of strategies that are based on the estimation of the counterpart’s
next offer, and give the predictive agent the advantage to establish agreements
that are more beneficial. An issue that is contemplated is that of risk when
employing a predictive strategy. A new strategy that permits the adoption of
different risk attitudes is proposed. This thesis also focuses on the AI-based
models used for prediction. The main problem of related applications is their
inability to capture the dynamics of turbulent negotiation environments, and
provide accurate estimations also in cases where data distributions change. For
this reason utilization of models that are based on data acquired from the
current discourse and adapt their structure in time are examined. More
specifically application of neural networks that adapt their structure on the
basis of a genetic algorithm, as well as a simple evolving connectionist
structure, eMLP, that does one-pass learning of data are developed and
assessed.
Keywords:
Electronic negotiations, Negotiating agents, Neural networks, Genetic algorithms, Predictive strategies
Number of index pages:
25-31
Number of references:
157
