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Download e-book for iPad: Advances in Robot Learning: 8th European Workshop on by Ulrich Nehmzow (auth.), Jeremy Wyatt, John Demiris (eds.)

By Ulrich Nehmzow (auth.), Jeremy Wyatt, John Demiris (eds.)

This publication constitutes the completely refereed post-workshop complaints of the eighth eu Workshop on studying Robots, EWLR'99, held in Lausanne, Switzerland in September 1999.
The seven revised complete workshop papers provided have been rigorously reviewed and chosen for inclusion within the booklet. additionally integrated are invited complete papers. one of the subject matters addressed are map construction for robotic navigation, multi-task reinforcement studying, neural community techniques, example-based studying, positioned brokers, making plans maps for cellular robots, course discovering, self reliant robots, and biologically encouraged approaches.

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Additional info for Advances in Robot Learning: 8th European Workshop on Learning Robots, EWLR-8 Lausanne, Switzerland, September 18, 1999 Proceedings

Example text

A POMDP agent can be decomposed into a state estimator SE and a policy π. 2 State Estimation When the agent is provided with a POMDP model of its environment and the agent uses the belief state as the state space on which to specify its policy, the key difficulty is that this state space is continuous and has as many dimensions as there are world states. This makes the task of finding an optimal POMDP control strategy computationally intractable. On the other hand, we have efficient computational techniques for solving (completely observable) Markov decision processes.

At the time of writing, only very few of these approaches have been applied to real robots [30]. Ring [25] defined continual learning as incremental, hierarchical development. He suggested that an agent should make use of previously learnt information Learning a Navigation Task in Changing Environments 25 when it has to learn a new behaviour. Moreover, the behaviours should be learnt in a bottom-up process whereby the old behaviours are used as constituents of newly created behaviours. In this work, we embrace these ideas and focus on two important problems of continual learning: the adaptability to changes in the environment and multi-task learning.

The Pioneer used in the experiments is also equipped with a 2 axis, 1 degree-of-freedom gripper. The robot control software runs off-board, on a remote UNIX workstation, with which the robot communicates through a radio link. The remote software receives status updates from the robot and its sonar sensors at a frequency of 10 Hz. The maximum command rate for changing the motion direction is only 2 Hz (or less) due to limitations of the on-board controller. The video images are also processed off-board.

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