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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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.
Download PowerPoint Presentation (512Kb ZIP file)
Future Internet
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Social Software is...

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.
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