Agent negotiation over multiple divisible resources with nonlinear utility functions under incomplete information

Agent negotiation over multiple divisible resources under incomplete information is a challenging task. Previous researches are mostly based on linear utility functions. However, lots of various instances show that the relationship between utilities and resources is usually saturated nonlinear, just as indicated by Wooldridge. To this end, we expand linear utility functions to nonlinear cases according to the law of diminishing marginal utility. Furthermore, we propose a negotiation model over multiple divisible resources with two phases. In the first phase, we take resources as indivisible units to reach a preliminary agreement which is the base of phase two at the same time. Sequentially, we divide resources using a greedy algorithm in the second phase to realize Pareto optimal results. The computational complexity of the proposed algorithm is proved to be polynomial order. Experimental results show that the optimal efficiency of the algorithm is distinctly higher than previous work.