KMi Seminars
Predicting Agents' Tactics in Automated Negotiation
This event took place on Monday 19 April 2004 at 13:00

Chongming Hou

In this talk, I will present a learning mechanism that applies nonlinear regression analysis to predict a negotiation agent?s behaviour based only the opponent's previous offers. The behaviour of negotiation agents in my study is determined by their tactics in the form of decision functions. Heuristics based on estimates of an agent?s tactics are drawn from a series of experiments. The findings of this empirical study show that this approach can be used to obtain better deals than existing decision function tactics. The learning mechanism can be used online, without any prior knowledge about the other agents and is therefore, very useful in open systems where agents have little or no information about each other.

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Our New Media Systems research theme aims to show how new media devices, standards, architectures and concepts can change the nature of learning.

Our work involves the development of short life-cycle working prototypes of innovative technologies or concepts that we believe will influence the future of open learning within a 3-5 year timescale. Each new media concept is built into a working prototype of how the innovation may change a target community. The working prototypes are all available (in some form) from this website.

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