Chess Game Tree Complexity and Memeplex Knowledge Graph Complexity
In the previous post I stated there is no way around to build an artificial Ego to be able to draw new conclusions. Of course there is, but I doubt such a machine will be build in my lifetime.
The game of chess has about 10^50 possible positions and about 10^120 possible games. To compute the whole game tree to find the perfect play was, is, and probable will always be not computeable on classic computers. We have the Quantum-Computers in pipe, and it is yet unknown if such a perfect-play engine is possible on such a machine. Current computer chess engines on von Neumann computers use heuristics to find the best move via an in depth limited tree search, and they do this meanwhile on a super-human level.
So, we can view our process of thinking similar to engines playing chess, we use our mind to search the memeplex knowledge graph for answers and solutions, we search the known graph we call knowledge, and we search the unknown what we call intuition, creativity and alike.
So, yes, in theory we can build a machine, maybe an Hyper-Meme-Machine, which expands the whole possible knowledge graph at once and runs some kind of evalution on possible candidates of new conclusions. All without the need of an artificial Ego.
The question which remains open is if such an SKGS, speculative knowledge graph search, can be implemented in practicable manner on our classic computers nowadays or near future.
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