Learning any memory-less discrete semantics for dynamical systems represented by logic programs

Learning from interpretation transition (LFIT) automatically constructs a model of the dynamics of a system from the observation of its state transitions. So far the systems that LFIT handled were mainly restricted to synchronous deterministic dynamics. However, other dynamics exist in the field of...

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Veröffentlicht in:	Machine learning Jg. 111; H. 10; S. 3593 - 3670
Hauptverfasser:	Ribeiro, Tony, Folschette, Maxime, Magnin, Morgan, Inoue, Katsumi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.10.2022 Springer Nature B.V Springer Verlag
Schlagworte:	Algorithms Artificial Intelligence Computer Science Control Dynamical systems Learning Logic Logic in Computer Science Logic programming Logic programs Machine Learning Mechatronics Modelling Natural Language Processing (NLP) Robotics Semantics Simulation and Modeling Special issue on Learning and Reasoning System dynamics Logical modeling Dynamic semantics Inductive logic programming Dynamic systems
ISSN:	0885-6125, 1573-0565
Online-Zugang:	Volltext
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