2 added 958 characters in body
source | link

I think we are a long way from understanding the kind of complexity which gives rise to cognition. For example one could argue "feedback" loops are key and some in fact have. But, deeper questions are unanswered by IIT or Tegmark's "upgrade". The most important is the relationship between cognitive complexity and time. Another is the nature of transformations which leave cognition invariant. I have addressed these issues in my paper, Causal Event Network:

http://xxx.tau.ac.il/abs/1402.7038

IIT is a statistical measure of complexity between two sets of random variables. Even if this measure is important to consciousness, the complexity comes about because of a transformation, a set of events in space and time. One can and I think should address the question of complexity directly on those event structures, on the process itself and not on the statistics which result from it. Cognitive processes, and hence our subjective experience can be viewed as transformation of information in space and time. Exploring the relationship between matter-energy and spacetime led us from the development of Classical Mechanics and Electro-Magnetism to the Standard Model of Physics and General Relativity. It is highly unlikely that without directly understanding how event structures relate to space and time we are able to understand the problem as they are more fundamental regardless of upgrades. In the above paper I present a possible point of view.

I think we are a long way from understanding the kind of complexity which gives rise to cognition. For example one could argue "feedback" loops are key and some in fact have. But, deeper questions are unanswered by IIT or Tegmark's "upgrade". The most important is the relationship between cognitive complexity and time. Another is the nature of transformations which leave cognition invariant. I have addressed these issues in my paper, Causal Event Network:

http://xxx.tau.ac.il/abs/1402.7038

I think we are a long way from understanding the kind of complexity which gives rise to cognition. For example one could argue "feedback" loops are key and some in fact have. But, deeper questions are unanswered by IIT or Tegmark's "upgrade". The most important is the relationship between cognitive complexity and time. Another is the nature of transformations which leave cognition invariant. I have addressed these issues in my paper, Causal Event Network:

http://xxx.tau.ac.il/abs/1402.7038

IIT is a statistical measure of complexity between two sets of random variables. Even if this measure is important to consciousness, the complexity comes about because of a transformation, a set of events in space and time. One can and I think should address the question of complexity directly on those event structures, on the process itself and not on the statistics which result from it. Cognitive processes, and hence our subjective experience can be viewed as transformation of information in space and time. Exploring the relationship between matter-energy and spacetime led us from the development of Classical Mechanics and Electro-Magnetism to the Standard Model of Physics and General Relativity. It is highly unlikely that without directly understanding how event structures relate to space and time we are able to understand the problem as they are more fundamental regardless of upgrades. In the above paper I present a possible point of view.

    Notice added Insufficient explanation by Joseph Weissman
1
source | link

I think we are a long way from understanding the kind of complexity which gives rise to cognition. For example one could argue "feedback" loops are key and some in fact have. But, deeper questions are unanswered by IIT or Tegmark's "upgrade". The most important is the relationship between cognitive complexity and time. Another is the nature of transformations which leave cognition invariant. I have addressed these issues in my paper, Causal Event Network:

http://xxx.tau.ac.il/abs/1402.7038