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AGENTS
1997
Springer
14 years 23 days ago
High-Level Planning and Low-Level Execution: Towards a Complete Robotic Agent
We have been developing Rogue, an architecture that integrates high-level planning with a low-level executing robotic agent. Rogue is designed as the oce gofer task planner for X...
Karen Zita Haigh, Manuela M. Veloso
HRI
2006
ACM
14 years 2 months ago
Teaching robots by moulding behavior and scaffolding the environment
Programming robots to carry out useful tasks is both a complex and non-trivial exercise. A simple and intuitive method to allow humans to train and shape robot behaviour is clearl...
Joe Saunders, Chrystopher L. Nehaniv, Kerstin Daut...
AGENTS
2001
Springer
14 years 1 months ago
Hierarchical multi-agent reinforcement learning
In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multi-agent tasks. We introduce a hierarchical multi-a...
Rajbala Makar, Sridhar Mahadevan, Mohammad Ghavamz...
ICML
2003
IEEE
14 years 9 months ago
Principled Methods for Advising Reinforcement Learning Agents
An important issue in reinforcement learning is how to incorporate expert knowledge in a principled manner, especially as we scale up to real-world tasks. In this paper, we presen...
Eric Wiewiora, Garrison W. Cottrell, Charles Elkan
ATAL
2010
Springer
13 years 9 months ago
Closing the learning-planning loop with predictive state representations
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon