By Pei Wang
This ebook presents the blueprint of a considering machine.While lots of the present works in man made Intelligence (AI) specialize in person facets of intelligence and cognition, the venture defined during this booklet, Non-Axiomatic Reasoning method (NARS), is designed and constructed to assault the AI challenge as a whole.This venture relies at the trust that what we name "intelligence" should be understood and reproduced as "the power of a method to evolve to its atmosphere whereas operating with inadequate wisdom and resources". in accordance with this concept, a singular reasoning process is designed, which demanding situations all of the dominating theories in how the sort of procedure might be equipped. The process contains out reasoning, studying, categorizing, making plans, determination making, etc., as diversified features of a similar underlying procedure. This thought additionally offers unified ideas to many difficulties in AI, good judgment, psychology, and philosophy.This publication is the main complete description of this decades-long undertaking, together with its philosophical starting place, methodological attention, conceptual layout info, its implications within the similar fields, in addition to its similarities and variations to many comparable works in cognitive sciences.
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Additional info for Rigid Flexibility: The Logic of Intelligence
We have collections of dumb specialists in small domains; the true majesty of general intelligence still awaits our attack. We have got to get back to the deepest questions of AI and general intelligence and quit wasting time on little projects that don’t contribute to the main goal. 24 Chapter 1 Wolfram made a similar comment [Stork, 1997a]: Nobody’s trying more fundamental stuﬀ. Everyone assumes it’s just too diﬃcult. Well, I don’t think there’s really any evidence of that. It’s just that nobody has tried to do it.
If someone insists that these works should be called AI simply because they solve problems that were previously solvable only by the human mind, then by the same token numerical calculating programs should be called AI, as well. Beside the issues of label and credit, the real problem of this approach is that it fails to explain why ordinary computer systems are not intelligent. Many people enter AI to look for a fundamentally diﬀerent way to build computer systems. To them, traditional computer systems are stupid, not because they cannot do anything (in fact, they can do many amazing things), but because they solve problems in a rigid manner.
The running of NARS consists of individual inference steps. In each step, a concept is selected probabilistically (according to its priority), then within the concept a task and a belief are selected (also probabilistically), and the applicable inference rules take the task and the belief as premises to derive new tasks and beliefs, which are added into the memory. The system runs continuously, and interacts with its environment all the time, without stopping at the beginning and ending of each task.
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