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→Reinforcement learning based on world models
The similarities and common features between the two fields can help us borrow ideas and techniques from one field to another. For example, an agent with a world model can interact with a complex system as a whole and obtain emergent causal laws from the interaction, thereby better helping us with the task of causal emergence identification. In turn, maximizing effective information technology can also be used in reinforcement learning to make the world model have stronger causal characteristics.
The similarities and common features between the two fields can help us borrow ideas and techniques from one field to another. For example, an agent with a world model can interact with a complex system as a whole and obtain emergent causal laws from the interaction, thereby better helping us with the task of causal emergence identification. In turn, maximizing effective information technology can also be used in reinforcement learning to make the world model have stronger causal characteristics.
===Other potential applications===
In addition to the above application fields, the causal emergence theory may have huge potential application value for other important issues. For example, it has certain prospects in the research of consciousness issues and the modern scientific interpretation of Chinese classical philosophy.
====Consciousness research====
First of all, the proposal of the causal emergence theory is greatly related to the research of consciousness science. This is because the core indicator of the causal emergence theory, effective information, was first proposed by Tononi in the quantitative theory of consciousness research, integrated information theory. After being modified, it was applied to Markov chains by Erik Hoel and the concept of causal emergence was proposed. Therefore, in this sense, effective information is actually a by-product of quantitative consciousness science.
Secondly, causal emergence, as an important concept in complex systems, also plays an important role in the research of consciousness science. For example, in the field of consciousness, a core question is whether consciousness is a macroscopic phenomenon or a microscopic phenomenon? So far, there is no direct evidence to show what scale consciousness occurs on. In-depth research on causal emergence, especially combined with experimental data of the brain nerve, may answer the question of the scale of occurrence of consciousness phenomena.
Thirdly, causal emergence may answer the question of free will. Do people have free will? Is the decision we make really a free choice of our will? Or is it possible that it is just an illusion? In fact, if we accept the concept of causal emergence and admit that macroscopic variables will have causal force on microscopic variables, then all our decisions are actually made spontaneously by the brain system, and consciousness is only a certain level of explanation of this complex decision-making process. Therefore, free will is an emergent downward causation. The answers to these questions await further research of the causal emergence theory.
====Chinese classical philosophy====
Different from Western science and philosophy, Chinese classical philosophy retains a complete and different theoretical framework for explaining the universe, including yin and yang, five elements, eight trigrams, as well as divination, feng shui, traditional Chinese medicine, etc., and can give completely independent explanations for various phenomena in the universe. For a long time, the two sets of philosophies in the East and the West have always been difficult to integrate. The idea of causal emergence may provide a new explanation to bridge the conflict between Eastern and Western philosophies.
According to the causal emergence theory, the quality of a theory depends on the strength of causality, that is, the size of <math>EI</math>. And different coarse-graining schemes will obtain completely different macroscopic theories (macroscopic dynamics). It is very likely that when facing the same research object of complex systems, the Western philosophical and scientific system gives a set of relatively specific and microscopic causal mechanisms (dynamics), while Eastern philosophy gives a set of more coarsely grained macroscopic causal mechanisms. According to the causal emergence theory or the Causal Equivalence Principle proposed by Yurchenko, the two are completely likely to be compatible with each other. That is to say, for the same set of phenomena, the East and the West can make correct predictions and even intervention methods according to two different sets of causal mechanisms. Of course, it is also possible that in certain types of problems or phenomena, a more macroscopic causal mechanism is more explanatory or leads to a good solution. For some problems or phenomena, a more microscopic causal mechanism is more favorable.
For example, taking the concept of five elements in Eastern philosophy, we can completely understand the five elements as five macroscopic states of everything, and the relationship of mutual generation and restraint of the five elements can be understood as a macroscopic causal mechanism between these five macroscopic states. Then, the cognitive process of extracting these five states of the five elements from everything is a coarse-graining process, which depends on the observer's ability to analogize. Therefore, the theory of five elements can be regarded as an abstract causal emergence theory for everything. Similarly, we can also apply the concept of causal emergence to more fields, including traditional Chinese medicine, divination, feng shui, etc. The common point of these applications will be that its causal mechanism is simpler and possibly has stronger causality compared to Western science, but the process of obtaining such an abstract coarse-graining is more complex and more dependent on experienced abstractors. This explains why Eastern philosophies all emphasize the self-cultivation of practitioners. This is because these Eastern philosophical theories put huge complexity and computational burden on '''analogical thinking'''.