Bilateral multi-issue negotiation model for a kind of complex environment

There are many uncertain factors in bilateral multi-issue negotiation in complex environments, such as unknown opponents and time constraints. The key of negotiation in complex environment is the negotiation strategy of Agent. We use Gaussian process regression and dynamic risk strategies to predict the opponent concessions, and according to the utility of the opponent’s offer and the risk function, predict the concessions of opponent, then set the concessions rate of our Agent upon the opponent's concession strategy. We run the Agent in Generic Environment for Negotiation with Intelligent multi-purpose Usage Simulation (GENIUS) platform and analyze the results of experiments. Experimental results show that the application of dynamic risk strategy in negotiation model is superior to other risk strategies.

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