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AAAI
2006
15 years 8 months ago
Reinforcement Learning with Human Teachers: Evidence of Feedback and Guidance with Implications for Learning Performance
As robots become a mass consumer product, they will need to learn new skills by interacting with typical human users. Past approaches have adapted reinforcement learning (RL) to a...
Andrea Lockerd Thomaz, Cynthia Breazeal
ICML
1998
IEEE
16 years 7 months ago
Genetic Programming and Deductive-Inductive Learning: A Multi-Strategy Approach
Genetic Programming (GP) is a machine learning technique that was not conceived to use domain knowledge for generating new candidate solutions. It has been shown that GP can bene ...
Ricardo Aler, Daniel Borrajo, Pedro Isasi
AAIP
2009
15 years 7 months ago
Incremental Learning in Inductive Programming
Inductive programming systems characteristically exhibit an exponential explosion in search time as one increases the size of the programs to be generated. As a way of overcoming ...
Robert Henderson
ASC
2006
15 years 6 months ago
Speeding up the learning of equivalence classes of bayesian network structures
For some time, learning Bayesian networks has been both feasible and useful in many problems domains. Recently research has been done on learning equivalence classes of Bayesian n...
Rónán Daly, Qiang Shen, J. Stuart Ai...
WOSP
1998
ACM
15 years 11 months ago
Poems: end-to-end performance design of large parallel adaptive computational systems
The POEMS project is creating an environment for end-to-end performance modeling of complex parallel and distributed systems, spanning the domains of application software, runti...
Ewa Deelman, Aditya Dube, Adolfy Hoisie, Yong Luo,...