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Integrating Axiomatic and Analogical Reasoning

Claes Strannegård (Institutionen för tillämpad informationsteknologi (Chalmers) ; Institutionen för filosofi, lingvistik och vetenskapsteori) ; Abdul Rahim Nizamani ; Ulf Persson (Institutionen för matematiska vetenskaper)
9th International Conference on Artificial General Intelligence, AGI 2016; New York; US; 16 - 19 July 2016, (Lecture Notes in Artificial Intelligence) Vol. 9782 (2016), p. 181-191.
[Konferensbidrag, refereegranskat]

We present a computational model of a developing system with bounded rationality that is surrounded by an arbitrary number of symbolic domains. The system is fully automatic and makes continuous observations of facts emanating from those domains. The system starts from scratch and gradually evolves a knowledge base consisting of three parts: (1) a set of beliefs for each domain, (2) a set of rules for each domain, and (3) an analogy for each pair of domains. The learning mechanism for updating the knowledge base uses rote learning, inductive learning, analogy discovery, and belief revision. The reasoning mechanism combines axiomatic reasoning for drawing conclusions inside the domains, with analogical reasoning for transferring knowledge from one domain to another. Thus the reasoning processes may use analogies to jump back and forth between domains.



Denna post skapades 2016-09-08. Senast ändrad 2016-12-06.
CPL Pubid: 241527

 

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Institutioner (Chalmers)

Institutionen för tillämpad informationsteknologi (Chalmers)
Institutionen för filosofi, lingvistik och vetenskapsteori (GU)
Institutionen för tillämpad informationsteknologi (GU) (GU)
Institutionen för matematiska vetenskaperInstitutionen för matematiska vetenskaper (GU)

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