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On the other hand, learning can often be brought on through overcoming some inconsistent circumstances. This paper proposes a framework for perpetual learning agents that are capable of continuously refining or augmenting their knowledge through overcoming inconsistencies encountered during their problem-solving episodes. The never-ending nature of a perpetual learning agent is embodied in the framework as the agent\u2019s continuous inconsistency-induced belief revision process. The framework hinges on the agents recognizing inconsistency in data, information, knowledge, or meta-knowledge, identifying the cause of inconsistency, revising or augmenting beliefs to explain, resolve, or accommodate inconsistency. The authors believe that inconsistency can serve as one of the important learning stimuli toward building perpetual learning agents that incrementally improve their performance over time.<\/p>","DOI":"10.4018\/jssci.2011100103","type":"journal-article","created":{"date-parts":[[2012,4,5]],"date-time":"2012-04-05T09:07:16Z","timestamp":1333616836000},"page":"33-51","source":"Crossref","is-referenced-by-count":10,"title":["Inconsistency-Induced Learning for Perpetual Learners"],"prefix":"10.4018","volume":"3","author":[{"given":"Du","family":"Zhang","sequence":"first","affiliation":[{"name":"California State University, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meiliu","family":"Lu","sequence":"additional","affiliation":[{"name":"California State University, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"jssci.2011100103-0","doi-asserted-by":"crossref","unstructured":"Banko, M., & Etzioni, O. (2007, October). 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