The Principle of Administrative Law and Judicial Application Based on E-commerce Model

Objectives: As a principle that controls the rational exercise of administrative power, the principle of proportionality is adopted by other legal systems because of its reasonable structure and effective control of administrative power. Methods: In this paper, in the information technology environment of mobile internet and based on the e-commerce model, the proportional principle of administrative law and its judicial application were studied. Results: Mainly the principle of proportionality in administrative law was introduced into the e-commerce negotiation system. A specific example in the context of e-commerce was selected to simulate the entire automatic negotiation process. Conclusion: The simulation experiment results were analyzed and summarized, which shows the advantages of the automatic negotiation mechanism proposed in this paper.

Study about Law Multi-Issue Automatic Negotiation Method Based on Artificial Intelligence and Multiagent Evolutionary Algorithm

Multiagent System (MAS) is a self-learning intelligent system formed by many single agents. Each agent in the MAS works independently of the other, and they have all the characteristics of an agent system. It can respond to changes and countermeasures based on its own external environmental conditions. When solving a complex problem, multiple agents can form a group to solve the problem together. In this paper, the agent’s evolutionary algorithm is integrated into the actual problem—multi-issue autonegotiation of law. According to this problem, the autonegotiation solution process and corresponding model are designed. In addition, a new type of solution is proposed for multiple legal issues. Compared with traditional solutions, the applicability has great advantages. Among them, the autonegotiation result of all the agent’s total utility can be quickly found. In the changing environment, this article focuses on the multiagent system negotiation problem. According to the distributed information sharing of multiple agents, even if the case reveals incomplete information, the multiagent can be generated while ignoring the incomplete information. Optimal solution is proposed. The experimental results show that the success rate of the system in analyzing multiple legal issues and autonegotiations reached 67.56% under the condition of incomplete information from the outside world.