On 9/27/19, Steve Richfield <[email protected]> wrote: > YKY, > > The most basic function of neurons is process control. That is where > evolution started - and continues. We are clearly an adaptive control > system. Unfortunately, there has been little study of the underlying > optimal "logic" of adaptive control systems. > > I strongly believe that a different sort of "logic" is at work, and that > what we call "intelligence" is simply a larger adaptive control system > working according to that "logic". We are clearly more intelligent than > ants, but that is more quantatative than qualitative. > > Learning logic seems like a good idea, but you might want to reconsider the > logic you are learning. > > Steve
Thanks for the comment. It is a very common objection indeed, and also has some good reasons behind it. >From cognitive psychology most people tend to believe that the brain uses *model-based* reasoning instead of *rules-based* reasoning. We don't fully understand the brain's mechanism, but we may guess at some general principles. I think the brain uses some sort of neural representations, which are composed of neural "*features*", ie, certain patterns of neurons' activations. Each neuron is either ON or OFF or may be regarded to activate with a fuzzy truth value. Thus we can view each neural feature as a "micro" *logic proposition*. That creates a rough correspondence between neural representations and logic representations. Indeed, it is not so surprising, as we can express our thoughts into natural language with relative ease, and natural language has the structure of logic propositions. For example, the visual cortex can recognize images such as "cat" and "dog". Through a dynamical process, it recognizes the situation of "cat chases dog". This is likely represented by a juxtaposition of "cat", "chase", "dog" neural features. This is very similar to the *predicate-logic* expression: chase(cat, dog). So there may not be a huge gap between neural and logical representations. The next question is: How does the brain jump from one neural representation state to the next? In logic, this is achieved via *rules with variables and quantifiers*. At this point I am not so sure if the brain's mechanism is really similar to the logical mechanism. That's why I think you raised a good question, and I still don't have a good answer 😊 , but it is a good place to start thinking. So I assume the brain jumps from one neural representation to the next, and that such neural states are formed via juxtaposition of "*concepts*" (which are some neural activation patterns). One way that this may be different from logic rules is that the neural representations can be "distributive". I need to think about this more, but there may exist a rough correspondence between logic rules and neural state-transitions. ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T77af318d4abfa8a8-M5869542b8bf0c880a6a68f3e Delivery options: https://agi.topicbox.com/groups/agi/subscription
