Artifical Intelligence (AI) are there for many years, but not as a comprehensive successful solution yet, due to the lack of measurement of intelligence and dynamics of intelligence.
Measurement plays critical roles in the development of dynamics: clock, telescope, microscope, etc. We even do not have a good way to measure intelligence now.
The concept Computational Complexity is used to measure computation, not intelligence. Current supercomputers already have comparable computing power and memory as human brains, but they are not even close to human intelligence now.
This is a clear indication: computation is different from intelligence, so Turing Machine and Computational Complexity Theory are not a right theoretic framework for intelligence and AI.
Turing Machine or equivalences, are actually highly influenced by deterministic models. Back to the dynamics for the real world, there are quantum theories, etc., which suggest the possibility of nondeterministism.
Some scientists tried to build the human mental models based on quantum theories. However, the difference between the time scale of neuron firing and excitations in microtubules and the decoherence time tells us there are some links in the middle still missing.
That is the reason I propose this three-level model: Life, Psychology, and Intelligence, to fit in the gap. Psychology is a subdomain of life, built on top of the other parts of life. Intelligence is a subdomain of both life and psychology, and built on top of the other parts of both life and psychology.
Ilya Prigogine's theory of systems far from equilibrium is a good foundation for life phenomena. My goal is to further study and accumulate the knowledge and models of psychology based on Brussels-Austin group and Ilya Prigogine's theories. Once concrete enough foundation has been constructed for this middleware, we coud combine the quantum theories and intelligence models.
So far, most of AI researches are based on methods of equilibrium. These approaches are difficult to make progresses in many areas. Probably people should try to re-focus AI researches on methods of far from equilibrium, rather than only on those of equilibrium.
There are some discussions of ontological aspect and epistemic aspect in Brussels-Austin approach. In real world, due to measurability, there could be several possibilities:
1) Measurable Determinism, determined by measurable factors: environment and internal states, etc.
2) Unmeasurable Determinism, determined by some factors which are not measurable.
3) Nondeterminism. With this model, there could be somethings such as free wills, etc.
Systems far from equilibrium, combined with the possibilities of measurable or unmeasurable, could be the way to illustrate the complexity of psychology and intelligence.
Based on my three-level model, the psychological concepts such as 'will' or 'free will' could be re-studied based on systems far from equilibrium. New concepts and models of intelliegnce could be proposed based on further studies.
Since life is a typical type of systems far from equilibrium, very different from other systems, Brussels-Austin group approach even could gain some hints from the studies based on my propsoal, to re-energize and push forward their research.
In this proposal, there are seven main points, if no one proposed them before, are my new contributions:
1) Propose the concept of Dynamics of Intelligence
2) AI fails as a comprehensive solution so far, due to the lack of measurement of intelligence and dynamics of intelligence.
3) Computation is different from intelligence. Computational complexity is used to measure computation, not intelligence. Turing Machine is not a right theoretic framework for artificial intelligence.
4) The difference between the time scale of neuron firing and excitations in microtubules and the decoherence time, does not exclude the possiblility to build psychology and intelligence models on quantum theories. Just people need build the missing middleware between them first.
5) The theories of far from equilibrium could be used as the foundation of the middleware mentioned in 3).
6) AI researches better to re-focus on methods of far from equilibrium, rather than only on those of equilibrium.
7) Brussels-Austin approach could use life phenomena as good study targets to gain hints, re-energize their efforts, and push forward the researches.
8) A three-level model for intelligence: Life, Psychology, and Intelliegnce. Psychology depends on the other parts of life. Intelligence depends on the other parts of both life and psychology.
If someone already proposed some or all of these ideas before, please let me know. I would really appreciate.
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