Constructivist Anticipatory Learning Mechanism ( CALM ) – dealing with partially deterministic and partially observable environments
暂无分享,去创建一个
Filipo Studzinski Perotto | Luis Otávio Alvares | Jean-Christophe Buisson | F. S. Perotto | J. Buisson | L. Alvares
[1] Filipo Studzinski Perotto,et al. Incremental Inductive Learning in a Constructivist Agent , 2006, SGAI Conf..
[2] Chris Thornton. Indirect sensing through abstractive learning , 2003, Intell. Data Anal..
[3] Charles Lee Isbell,et al. Schema Learning: Experience-Based Construction of Predictive Action Models , 2004, NIPS.
[4] Risto Miikkulainen,et al. The constructivist learning architecture: a model of cognitive development for robust autonomous robots , 2004 .
[5] L. Suchman. Plans and situated actions , 1987 .
[6] Charles Lee Isbell,et al. Looping suffix tree-based inference of partially observable hidden state , 2006, ICML.
[7] Marco C. Bettoni,et al. Made-Up Minds: A Constructivist Approach to Artificial Intelligence , 1993, IEEE Expert.
[8] Paul A. Crook,et al. Learning in a State of Confusion: Perceptual Aliasing in Grid World Navigation , 2003 .
[9] Pat Langley,et al. Selection of Relevant Features and Examples in Machine Learning , 1997, Artif. Intell..
[10] J. Piaget. The construction of reality in the child , 1954 .
[11] Ronald L. Rivest,et al. Diversity-based inference of finite automata , 1994, 28th Annual Symposium on Foundations of Computer Science (sfcs 1987).
[12] T. Oates,et al. Grounding the Unobservable in the Observable: The Role and Representation of Hidden State in Concept Formation and Refinement , 2001 .
[13] Peter Stone,et al. Learning Predictive State Representations , 2003, ICML.
[14] Andreas Birk,et al. Schemas and Genetic Programming , 2000 .