In recent years, the Alpha series, an outstanding representative of AI, has achieved dazzling results in games such as Go, but its roots are still related machine learning and reasoning under closed conditions, while the roots of intelligent games are still causality and inference in open environments. The learning and understanding of people with mixed relevance. This learning can produce tacit knowledge and order rules with a certain degree of uncertainty (just like children’s learning). This understanding can relate seemingly irrelevant things. stand up. Various signs indicate that the future game may be a system of integration of human-machine environment systems.
Sun Tzu said: Knowing the enemy and confidant will never end every battle. The knowledge here includes both human perception and machine perception. The difference between human and machine perception is that humans can get lost in their minds, and machines can’t understand intentions as flexibly and deeply as humans; here they include both opponents and machines. Equipment and environment, the self here also includes its own human, machine, and environment. Therefore, without people, there is no intelligence, there is no artificial intelligence, and there is no future war. True intelligence or artificial intelligence cannot be achieved by an abstract mathematical system. Mathematics is only a tool. It can only achieve functions, not capabilities. Only humans can produce real capabilities. Therefore, artificial intelligence is human, machine, A product of the interaction of environmental systems, future games will also be the result of machine calculations combined with human calculations. It is a combination of calculations or insights. In fact, if it is only a simple calculation, the faster and more accurate the calculation will be. The more intelligent, the greater the danger, the easier it is to be deceived, and the easier it is to "be clever against being mistaken by cleverness". A well-known Chinese idiom "to lose one's horse" shows that calculation is inferior to human calculation and insight.
Recently, some countries have proposed multi-domain, global, mosaic and other modes for future game methods. These are human-machine environmental systems engineering, which are the dispersion and aggregation of various elements in human, machine, and environment, and are a variety of symbols. Distributed representational computing is integrated, mixed, and fused with many non-symbolic phenomenological representations. It is also a cross-complementation of machinery, information, knowledge, experience, artificial intelligence, intelligence, and wisdom.
Therefore, the human-machine fusion intelligent mechanism and the cracking of the mechanism will become the key to winning the game in the future. Any division of labor will be limited by scale and scope. The function allocation in human-machine integrated intelligence is part of the division of labor, and the other part is capacity allocation. Function allocation is passive and caused by external demand; capacity allocation is active and generated by internal drive. In complex, heterogeneous, unstructured, non-linear data/information/knowledge, human or human-like directional preprocessing is very important. When the problem domain is initially reduced, the machine has the advantages of bounded, fast and accurate It can be played out; in addition, when a large amount of data/information/knowledge is obtained, the machine can also initially map them to several fields, and then humans can further process and analyze. The assimilation and cross-balance of these two processes is roughly the process of organic integration of man and machine.
The future game is not only an intelligent game, but also an intelligent game. The future game will not only break the formal mathematical calculations, but also break the logical calculations of traditional thinking. It is a way of combining the advantages of people, machines, and the environment. New calculation-calculation game system. This is a bit like education. The task of a school is to teach knowledge to students (a bit like machine learning), but education is not just to teach knowledge. Education should dig out the logic behind knowledge, or something deeper. For example, when we teach calculations, we actually have to think about what is behind the calculations. We should first cultivate students' sense of number, then teach them the concept of calculation, what is addition and what is subtraction, and then teach how to apply it to form insight.
In the intelligent game, the cooperative game is a necessary means. In view of the continuous spread and proliferation of nuclear weapons, the cost of future games between countries will become higher and higher, regardless of their size. From a certain perspective, the two are both partners, competitors and strategic opponents (not only to prevent nuclear/biochemical/intelligent systems from getting out of control, but also to destroy the other's will and defeat the opponent). If you regard men as power and women as wisdom, then the future game should be a feminine war, at least a mixed game.
No matter how artificial intelligence develops, the future belongs to mankind. It is up to mankind to jointly define the rules of the future game and determine the fate of artificial intelligence, not artificial intelligence to determine the fate of mankind. The reason is that artificial intelligence is logical, and future games are not only logical, there are also a lot of non-logical factors. In the face of the strong electromagnetic spectrum and cyberspace gaming capabilities of the other party, when various forces cooperate in the implementation of multi-domain games, the seamless connection and coordination of various systems such as information communication, command and control systems, intelligence, surveillance, and reconnaissance will also be one. Big test.
Therefore, the future game is an intelligent collaborative game mode that effectively combines man-machine environment and cooperates with multiple fields.