Computer Science ›› 2015, Vol. 42 ›› Issue (1): 220-226.doi: 10.11896/j.issn.1002-137X.2015.01.049

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Learning Action Models Described in Action Language B by Combining ILP and ASP

LIU Zhen and ZHANG Zhi-zheng   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Action model learning is beneficial to autonomous and automated systems.If an Agent can update its action model according to the changes occurred in the environment,it can be more adaptable to the world and operate more effectively.Simultaneously,action model learning can provide modeling dynamic domain with an initial rough model which is the foundation for further improvement and modification.We designed an algorithm used for learning action models described in language B by combining ILP and ASP.This algorithm can work on dynamic domains consisting of objects of different scale.In the experiments,we tested the learning algorithm through using classic planning cases and verified the soundness of the learning algorithm.

Key words: Action model learning,Action language B,Inductive logic programming,Answer set programming

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