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» Introducing Actions into Qualitative Simulation
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FLAIRS
2004
13 years 9 months ago
State Space Reduction For Hierarchical Reinforcement Learning
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
Mehran Asadi, Manfred Huber
IJCAI
2003
13 years 9 months ago
Simultaneous Adversarial Multi-Robot Learning
Multi-robot learning faces all of the challenges of robot learning with all of the challenges of multiagent learning. There has been a great deal of recent research on multiagent ...
Michael H. Bowling, Manuela M. Veloso
ICRA
2009
IEEE
179views Robotics» more  ICRA 2009»
14 years 2 months ago
Automatic weight learning for multiple data sources when learning from demonstration
— Traditional approaches to programming robots are generally inaccessible to non-robotics-experts. A promising exception is the Learning from Demonstration paradigm. Here a polic...
Brenna Argall, Brett Browning, Manuela M. Veloso
ICRA
2009
IEEE
132views Robotics» more  ICRA 2009»
14 years 2 months ago
Smoothed Sarsa: Reinforcement learning for robot delivery tasks
— Our goal in this work is to make high level decisions for mobile robots. In particular, given a queue of prioritized object delivery tasks, we wish to find a sequence of actio...
Deepak Ramachandran, Rakesh Gupta
COSIT
2009
Springer
146views GIS» more  COSIT 2009»
14 years 2 months ago
Decentralized Time Geography for Ad-Hoc Collaborative Planning
For an autonomous physical agent, such as a moving robot or a person with their mobile device, performing a task in a spatio-temporal environment often requires interaction with ot...
Martin Raubal, Stephan Winter, Christopher Dorr