15 Jul From Perception and Learning to Logic
Perception and Learning
I am not a cognitive scientist, so all I have said in this section is based on the work of others. On the other hand, I have probably spent more time seriously studying cognition than most computer geeks, and I have tried to form my perspectives around the best of our knowledge. The posts contain a few points that support my world view and my ideas about how to build smarter systems. Here is a summary of my points in this section:
- Posts 1-5: The brain and the sensory organs give us specialized ways of recognizing different patterns of input stimuli across all five senses.
- Posts 6-10: Beginning during fetal development, humans establish complex mechanisms for receiving and responding to input stimuli, enabling conscious interaction with our changing environment
- Posts 11-15: Learning occurs as repeated observation of visual and other patterns form lasting connections in our brains, from very simple patterns of shape and color to complex patterns of cause and effect
- Posts 16-20: Recognition involves neural patterns of activation that heat up areas of prior knowledge associated with the patterns we observe, enabling us to infer properties of things we’ve never seen before
- Posts 21-25: We remember things in the context of perceived sights, sounds, smells and textures, enabling us to develop complex contextual views of how the world is or should be
|Understanding Context Cross-Reference|
|Click on these Links to other posts and glossary/bibliography references|
|Prior Post||Next Post|
|Gnosticism Mysticism and Hard Knowledge||Fuzzy Logic Section Intro|
|brain sensory specialization||Cognitive Science References|
|pattern recognition||Minsky 1986 Gardner 1985|
|input stimulus consciousness||Baumgartner 1995 Dennett 1991|
The software of thought (cognition) is probably the most complex system known to man. And it runs on the most complex hardware known to man: the brain. We perceive. The things we perceive enable us to recognize, then reason, about things in the world. Events we perceive enable us to reason abstractly about the nature of very abstract things in the universe such as time, distance, cause and effect, good and bad. We can even use our reasoning faculties to predict the future, immediate and otherwise, with remarkable success.
Abstract things like time, distance, good and bad can be described using scales. A continuum (such as bad to good) represents an abstract judgement that we can use on anything applicable. A time continuum is used to represent a historical line on which we may place events in sequence. A distance continuum is useful for travel, calculating shipping costs and durations, and many other cognitive tasks.
As we learn, we classify things in hierarchies, and seek to find the causes of events. Hierarchical and causal reasoning, as well as temporal and spatial reasoning, will be covered in greater depth in the next section of Understanding Context.
If your objective is to make a mechanical brain, the information in this section of posts should have helped you understand some of the key requirements for the model, especially on the front end of the process in which patterns of interest are ingested and remembered.
In the subject index of the bibliography you will find applicable references under the following topics:
Here are some great references in this subject area:
|Click below to look in each Understanding Context section|
|4||Perception and Cognition||5||Fuzzy Logic||6||Language and Dialog||7||Cybernetic Models|
|8||Apps and Processes||9||The End of Code||Glossary||Bibliography|