Difference between revisions of "ArtificialIntelligenceResearch"
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| − | * | + | * [http://www.thoughtbecomesreality.com/images/MindModel.jpg link] |
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| − | * | + | * [http://www.ethics.org.au/resources/img/general-content/holistic-ethics-model.gif link] |
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| − | * | + | * [http://perspicuity.net/common/a-mind.jpg link] |
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| − | * | + | * [http://www.anth.uconn.edu/faculty/dandrade/assets/model-of-the-mind.gif link] |
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== Interesting Things == | == Interesting Things == | ||
| − | * MFA controllers are ideal for environmental simulation and test control. Avoiding process models means lower development costs and faster time to market, more robust and precise control means better lab test results, and no manual tuning means lower operating costs and longer up time - see | + | * MFA controllers are ideal for environmental simulation and test control. Avoiding process models means lower development costs and faster time to market, more robust and precise control means better lab test results, and no manual tuning means lower operating costs and longer up time - see [http://cybosoft.net/technologies/mfaoverview.html mfaoverview.html] |
== Useful resources == | == Useful resources == | ||
docs: | docs: | ||
| − | # | + | # [http://www.cs.ualberta.ca/~sutton/book/ebook/the-book.html Reinforcement Learning: Introduction] |
| − | # | + | # [http://scienceblogs.com/developingintelligence Journal: Developing Intelligence] |
| − | # | + | # [http://www.aaai.org/AITopics/pmwiki/pmwiki.php/AITopics/CognitiveScience AAAI: Congnitive Science] |
| − | # | + | # [http://www.numenta.com/Numenta_HTM_Concepts.pdf Hierarchical Temporal Memory, pdf] |
video: | video: | ||
| − | # | + | # [http://video.google.com/videoplay?docid=-2500845581503718756 HTM by Jeff Hawkins - Hierarchical Temporal Memory: Theory and Implementation] |
| − | # | + | # [http://mitworld.mit.edu/video/484 Way of thinking model - Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human] |
| − | # | + | # [http://www.youtube.com/watch?v=HVGlfcP3ATI Mind Components] |
Revision as of 10:21, 17 June 2015
Artificial Intelligence Research
@@Home -> ArtificialIntelligenceResearch
Artificial Intelligence research covers approaches of constructing intelligence feature which is somehow like biological one, by means of software program.
Terms
- artificial intelligence: a characteristic, enabling full replacement of a human for a specific subset of human functions
Research targets
See research status grouped by target
- Associative Memory
- Emotional Machine (suppressing mind areas instead of adding smth) ==
- Find whether Semantic Networks can help
- Evaluate reinforcement learning to allow learn state-to-action strategies
- Choose a model for low-level associative memory
- Evaluate Hierarchical Temporal Memory to create recognition engine
- Create a reasonable mind model, starting from draft in Vision
- Equivalence to biological brain.
external examples:
Interesting Things
- MFA controllers are ideal for environmental simulation and test control. Avoiding process models means lower development costs and faster time to market, more robust and precise control means better lab test results, and no manual tuning means lower operating costs and longer up time - see mfaoverview.html
Useful resources
docs:
# Reinforcement Learning: Introduction # Journal: Developing Intelligence # AAAI: Congnitive Science # Hierarchical Temporal Memory, pdf
video:
# HTM by Jeff Hawkins - Hierarchical Temporal Memory: Theory and Implementation # Way of thinking model - Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human # Mind Components
