Two methodologies to build AI
There are two streams in the methodology of AI construction: Symbolism and Connectionism, depends on which point of intelligence is set as model. They have a significant difference: Symbolism requires the substance of “intelligence” in the “reasoning” actions, while Connectionism does so in “consciousness” (or in “recognition” based on it).
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・”Symbol” and “Leaning”
While AI in Symbolism attempts to implement a complete "intelligence" called a “program” from the beginning, "intelligence" in Connectionism assumes that it becomes mature through the accumulation of recognition and conscious actions; which interpreted as “learning” from experiences.
Since Symbolism is based on the "inference" model, it has to establish "Symbol" as a medium between AI and the world. In contrast, in Connectionism, the world is directly connected with AI in the form of "recognition" to "target."
・17th and 20th Centuries
Symbolism is an approach which traces back to the Universal Symbolism Project by a 17th century philosopher, Leibniz (who attempted to automate thinking by developing an ideal artificial language that can systematically symbolize the reasoning process) (A Philosopher invented AI, https://society-zero.com/chienotane/archives/8267#6 ).
Connectionism, on the other hand, was born in the 20th century to understand human’s intellectual behaviors based on the function of cranial nerve system, which organizes itself by creating "Connections.” It comes from the fusion of psychology, neuro-brain science, computer science, mathematics, and linguistics. It aims to artificially realize the advanced information processing functions in the brain, by learning from the information processing modes of nerve cells (neuron) and neural networks in the organism brain.
Deep learning, which has recently came into the spotlight, is one of the artifacts of the Connectionism approach. In the production of game characters, due to the demands for AI with a body, the task of physical intelligence: intelligence rooted in the organism body: is within range, and the affordance as academic achievement is being utilized.
Check out Resources (books) for more for symbolism, connectionism, and affordance.
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【Reference (books) List】
(For more information about the book, click the book title. If you click on the related knowledge card that is under the book title, you can see the context in which these books are selected for reference, which are very useful for an Active Learner.)
Deep Learning (Adaptive Computation and Machine Learning series)
・Connectionism／https://society-zero.com/icard/679605
Artificial Intelligence: A Modern Approach, Global Edition (English Edition) 3rd Edition
・Symbolism／https://society-zero.com/icard/715363
・The Symbol Grounding Problem and AI (1)／https://society-zero.com/icard/510595
・Connectionism／https://society-zero.com/icard/679605
言語と身体性
・The Symbol Grounding Problem and AI (1)／https://society-zero.com/icard/510595
・The Symbol Grounding Problem and AI (2)／https://society-zero.com/icard/876700
アフォーダンス入門
・Affordance and AI／https://society-zero.com/icard/542948
ビッグデータと人工知能
・The Symbol Grounding Problem and AI (1)／https://society-zero.com/icard/510595
生態心理学の構想
・Ecological AI／https://society-zero.com/icard/491197
絵でわかる人工知能
・Symbolism and Connectionism／https://society-zero.com/icard/823321
人工知能のための哲学塾
・The Symbol Grounding Problem and AI (2)／https://society-zero.com/icard/876700
・Connectionism／https://society-zero.com/icard/679605
・Ecological AI／https://society-zero.com/icard/491197
マッチ箱の脳（AI）
・Connectionism／https://society-zero.com/icard/679605
◎This is a listing of Reference "Chapter 3: Two Ways of Creating Artificial Intelligence" of 'Artificial Intelligence and Artificial Intellect (Youichiro Miyake)'.
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