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JAIR
2000
102views more  JAIR 2000»
15 years 3 months ago
A Model of Inductive Bias Learning
A major problem in machine learning is that of inductive bias: how to choose a learner's hypothesis space so that it is large enough to contain a solution to the problem bein...
Jonathan Baxter
ATAL
2009
Springer
15 years 10 months ago
MABLE: a framework for learning from natural instruction
The Modular Architecture for Bootstrapped Learning Experiments (MABLE) is a system that is being developed to allow humans to teach computers in the most natural manner possible: ...
Roger Mailler, Daniel Bryce, Jiaying Shen, Ciaran ...
AIPS
1998
15 years 4 months ago
Planning, Execution and Learning in a Robotic Agent
This paper presents the complete integrated planning, executing and learning robotic agent Rogue. We describe Rogue's task planner that interleaves high-level task planning w...
Karen Zita Haigh, Manuela M. Veloso

Publication
240views
14 years 1 months ago
Bayesian multitask inverse reinforcement learning
We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or ...
Christos Dimitrakakis, Constantin A. Rothkopf
162
Voted
ICRA
2009
IEEE
169views Robotics» more  ICRA 2009»
15 years 10 months ago
Task-level imitation learning using variance-based movement optimization
— Recent advances in the field of humanoid robotics increase the complexity of the tasks that such robots can perform. This makes it increasingly difficult and inconvenient to ...
Manuel Mühlig, Michael Gienger, Sven Hellbach...