Title: Automated negotiation with behaviour prediction

Authors: Mohammad Irfan Bala; Sheetal Vij; Debajyoti Mukhopadhyay

Addresses: Maharashtra Institute of Technology, Pune 411038, India ' Maharashtra Institute of Technology, Pune 411038, India ' Maharashtra Institute of Technology, Pune 411038, India

Abstract: The proliferation of web technologies has made it increasingly important to make the traditional negotiation pricing mechanism automated and intelligent. Negotiation is although a complex activity to automate without human intervention but the software agents when enhanced with learning techniques can better simulate the human intelligence and increase the profits of their owners. Prediction of partner's behaviour in negotiation will not only improve the utility gain for the adaptive negotiation agent but also achieve the agreement much quicker. The basic concept is that the information about negotiators, their individual actions and dynamics can be used by software agents who are equipped with adaptive capabilities so that they can learn from past negotiations and provide assistance for selection of appropriate negotiation tactics. In this paper an automated negotiation system has been proposed which is capable of predicting the strategy and the preferences of the opponent.

Keywords: automated negotiation; prediction; software agents; negotiation tactics; pricing negotiation; partner behaviour; multi-agent systems; MAS; agent-based systems.

DOI: 10.1504/IJIPT.2015.074339

International Journal of Internet Protocol Technology, 2015 Vol.9 No.1, pp.44 - 50

Received: 22 Nov 2014
Accepted: 01 Nov 2015

Published online: 22 Jan 2016 *

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