In this paper, basing on the grey system theory with "partial information be known, partial information be unknown" of "small sample", "poor information" uncertainty system as researching object.From the basis of historical data to build models, the price of house and from the background value of improvement is given and the primary value of the two aspects from the selection of optimization of the improved model, using the residual value, poor development coefficient, posterior ratio and the small error is probable to the improved model.

This paper focuses on the rational distribution of task utilities in coalition skill games, which is a restricted form of coalition game, where each service agent has a set of skills and each task agent needs a set of skills in order to be completed. These two types of agents are assumed to be self-interested. Given the task selection strategy of service agents, the utility distribution strategies of task agents play an important role in improving their individual revenues and system total revenue. The problem that needs to be resolved is how to design the task selection strategies of the service agents and the utility distribution strategies of the task agents to make the self-interested decisions improve the system whole performance. However, to the best of our knowledge, this problem has been the topic of very few studies and has not been properly addressed. To address this problem, a task allocation algorithm for self-interested agents in a coalition skill game is proposed, it distributes the utilities of tasks to the needed skills according to the powers of the service agents that possess the corresponding skills. The final simulation results verify the effectiveness of the algorithm.

In practical applications, there are many task allocation problems involving the participation of self-interested agents, including Witkey, crowdsourcing and electronic markets. In these cases, to improve the efficiency of task allocation, a reasonable distribution of utilities is critical. To the best of our knowledge, few studies have examined the complex task allocation and utility distribution of self-interested agents, and good solutions are lacking. To address this issue, the following works are done in this paper: first, based on a task allocation model for self-interested agents and by studying the Nash bargaining solution and the bargaining characteristics of the agents, an efficiency utility distribution algorithm satisfying individual rationality and budget effectiveness is proposed. Second, based on the best response strategy of the self-interested agent, a complex task allocation algorithm for multiple self-interested agents is proposed. Finally, the effectiveness of the proposed algorithm is verified by comparing the system revenues with other utility distribution and task allocation algorithms.

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