Current Issue : October-December Volume : 2022 Issue Number : 4 Articles : 5 Articles
Digital games are various games designed and developed with digital technology and implemented on digital equipment. With the active development of the modern game industry, related technologies such as real-time graphics rendering, realistic interaction, and artificial intelligence of games are also constantly improving. Among them, the artificial intelligence technology of games is limited by the development of theoretical artificial intelligence and the calculation time of real-time systems, and the development lags behind graphics and interactive technology. In order to solve these problems, this paper proposes the application of artificial intelligence in digital games based on mathematical statistics methods, aimed at studying and improving the intelligence level of digital games. The method of this paper is to study the mathematical statistics method and the basic principle of Sarsa learning algorithm and then propose the technology of artificial intelligence applied to digital games. The role of these methods is to study different types of mathematical statistics, to study the behavioral tree of artificial intelligence in digital games and the development prospects of the game, and to update the value of artificial intelligence in each iteration according to the Sarsa algorithm formula. This paper proposes a decision-making system to improve the intelligence level of digital games by analyzing the research status of digital games and the mathematical statistics of basketball digital games. In the basketball game experiment, the difference between the operation data of the decision-making system proposed in this paper and the operation data of human players in five game items reaches 0.51, 0.83, 0.58, 0.49, and 0.78, respectively....
“Carbon peak and neutrality” are an important strategic decision to promote the transformation of China’s energy economy and build a community with a shared future for mankind. China is a big energy consumer, and the whole society is facing huge challenges under the goal of carbon peak and neutrality. The realization of the goal of carbon peak and neutrality requires the guidance of correct theoretical methods and scientific deployment. This paper mainly studies the energy consumption scheduling, demand response management, and energy trading problems of microgrid. In view of the shortcomings of the existing energy optimization scheduling methods in the microgrid, a variety of energy resources such as electric energy, natural gas, heat energy, and cold energy are considered into the microgrid model. Based on the noncooperative game and Stackelberg game, a new energy optimal dispatch model is constructed with a variety of game methods such as two-layer game. Maximize the personal benefits of the microgrid while meeting the reliable operation of the system and the electricity demand of users. The three-stage noncooperative game problem is solved based on the reverse bootstrap method, and the closed expression of the optimal strategy in each stage is obtained. The power generation forecasting technology based on big data is studied, and a power forecasting method is proposed, which can effectively guide the energy consumption of the microgrid. The simulation results show the effectiveness of the proposed renewable energy management model based on big data, which verifies that the accurate wind power prediction results are conducive to better theoretical analysis of energy management....
In order to improve the intelligence of the next-generation game model, a new game artificial intelligence came into being. Through the in-depth understanding and research of the next generation of game model production technology, the current industry general production process is summarized, and a set of effective production methods is expounded. In the context of the rapid development of digital technology, the game industry increasingly recognizes the importance of digital carving technology for the design and production of the next generation of games. The design and production of the next-generation game model can make up for the lack of refinement of the traditional next-generation game character model and the unreal mapping effect. This paper focuses on two ways: behavior tree and machine learning, designing game AI with more anthropomorphic perception and flexible behavior. Finally, the basketball player competition AI designed with a behavior tree and machine learning demonstrates its intelligent behavior....
In order to overcome the defect that sparrow search algorithm converges very fast but is easy to fall into the trap of local optimization, based on the original mechanism of sparrow algorithm, this paper proposes game predatory mechanism and suicide mechanism, which makes sparrow algorithm more in line with its biological characteristics and enhances the ability of the algorithm to get rid of the attraction of local optimization while retaining the advantages of fast convergence speed. By initializing the population with the good point set strategy, the quality of the initial population is guaranteed and the diversity of the population is enhanced. In view of the current situation that the diversity index evaluation does not consider the invalid search caused by individuals beyond the boundary in the search process, an index to measure the invalid search beyond the boundary in the search process is proposed, and the measurement of diversity index is further improved to make it more accurate. The improved algorithm is tested on six basic functions and CEC2017 test function to verify its effectiveness. Finally, the improved algorithm is applied to the three-dimensional path planning of UAV with threat area. The results show that the improved algorithm has stronger optimization performance, has strong competitiveness compared with other algorithms, and can quickly plan the effective and stable path of UAV, which improves an effective method for the application in this field and other fields....
With the implementation of a series of preferential strategies by online car-hailing companies, the contradiction between online car-hailing and traditional taxis and passengers has become more and more intense. Coordinating the interests of the three parties has become increasingly important. In order to coordinate the contradiction between online car-hailing and traditional taxis and passengers and to manage the online car-hailing and traditional taxis reasonably, this paper conducts research on the operation and management strategy of online car-hailing platform based on big data diagnosis and game perspective. In order to solve the problem of online car-hailing platform operation and management strategy, this paper adopts a research method combining qualitative judgment and quantitative analysis and conducts research by combining specific logic deduction, field investigation, empirical research, mathematical analysis, and computer simulation. The results found that while the platform rate was reduced to 0.085, the daily income of online motorists increased from 170 yuan to 236 yuan, by 38.6%. In the event of a reduction in taxi fares to -3500, one hire the daily income of motorists increased from 134 yuan to 212 yuan, an increase of 57.8%. This shows that reducing the percentage of the platform has the greatest impact on the revenue of online car-hailing companies, and the recharge rebate strategy has the least impact on the revenue of online car-hailing companies. The strategy of reducing elementary money concessions can greatly increase the income of taxi drivers, but it also reduces nearly one-third of the income of taxi companies....
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