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ICML
2002
IEEE
15 years 10 months ago
Reinforcement Learning and Shaping: Encouraging Intended Behaviors
We explore dynamic shaping to integrate our prior beliefs of the final policy into a conventional reinforcement learning system. Shaping provides a positive or negative artificial...
Adam Laud, Gerald DeJong
ICRA
2007
IEEE
157views Robotics» more  ICRA 2007»
15 years 4 months ago
Learning to Select State Machines using Expert Advice on an Autonomous Robot
— Hierarchical state machines have proven to be a powerful tool for controlling autonomous robots due to their flexibility and modularity. For most real robot implementations, h...
Brenna Argall, Brett Browning, Manuela M. Veloso
FOCS
1994
IEEE
15 years 2 months ago
The Power of Team Exploration: Two Robots Can Learn Unlabeled Directed Graphs
We show that two cooperating robots can learn exactly any strongly-connected directed graph with n indistinguishable nodes in expected time polynomial in n. We introduce a new typ...
Michael A. Bender, Donna K. Slonim
ETVC
2008
14 years 11 months ago
Intrinsic Geometries in Learning
In a seminal paper, Amari (1998) proved that learning can be made more efficient when one uses the intrinsic Riemannian structure of the algorithms' spaces of parameters to po...
Richard Nock, Frank Nielsen
GEOINFORMATICA
1998
96views more  GEOINFORMATICA 1998»
14 years 9 months ago
Experiments with Learning Techniques for Spatial Model Enrichment and Line Generalization
The nature of map generalization may be non-uniform along the length of an individual line, requiring the application of methods that adapt to the local geometry and the geographi...
Corinne Plazanet, Nara Martini Bigolin, Anne Ruas