Research on the Optimization Model of Digital Resource Allocation in Cultural and Tourism Industry Based on Reinforcement Learning

This paper intends to introduce the multi-intelligence of digital resources in cultural and tourism industry in reinforcement learning.In order to scientifically evaluate digital resource allocation, the index system characterizing resource allocation is constructed using hierarchical analysis.From there, a multi-objective collaborative optimization allocation model of digital resources in cultural and tourism industry based on reinforcement learning and multi-intelligent body system is established.Through empirical analysis, it can be seen that referring to the observation of the development of the comprehensive level of digital resource allocation, there is an imbalance in the development level of N province.The indicator system is refined to consist of 4 guideline level indicators and 26 indicator level indicators.Before and after the multi-objective synergistic optimization, the total amount of digital resource procurement for the cultural and tourism industry in province N was reduced by 460,742 yuan.After optimization, the comprehensive efficiency of resource allocation in area a improves by 0.03136, area b improves by 0.03275, and area h improves by 0.02799.Moreover, all of them tend to be in equilibrium.Therefore, the multi-objective synergistic optimization allocation model in this paper can improve the efficiency of digital resources in cultural tourism industry and reduce the differences between districts and counties.