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» Approximate Learning of Dynamic Models
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118
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ICRA
2008
IEEE
197views Robotics» more  ICRA 2008»
15 years 9 months ago
Approximate optimal control of the compass gait on rough terrain
Abstract— In this paper, we explore the capabilities of actuated models of the compass gait walker on rough terrain. We solve for the optimal high-level feedback policy to negoti...
Katie Byl, Russ Tedrake
AI
1999
Springer
15 years 2 months ago
Cooperative Behavior Acquisition for Mobile Robots in Dynamically Changing Real Worlds Via Vision-Based Reinforcement Learning a
In this paper, we first discuss the meaning of physical embodiment and the complexity of the environment in the context of multi-agent learning. We then propose a vision-based rei...
Minoru Asada, Eiji Uchibe, Koh Hosoda
103
Voted
JAIR
2011
187views more  JAIR 2011»
14 years 9 months ago
A Monte-Carlo AIXI Approximation
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...
134
Voted
ICSTM
2000
164views Management» more  ICSTM 2000»
15 years 4 months ago
Building Sustainable Interest in Modelling in the Classroom
System Dynamics has had a tough time breaking into High Schools. Like all good ideas the most difficult part is convincing those who would most benefit that this new approach is i...
Gordon Kubanek
166
Voted
ML
2002
ACM
246views Machine Learning» more  ML 2002»
15 years 2 months ago
Bayesian Clustering by Dynamics
This paper introduces a Bayesian method for clustering dynamic processes. The method models dynamics as Markov chains and then applies an agglomerative clustering procedure to disc...
Marco Ramoni, Paola Sebastiani, Paul R. Cohen