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» Learning humanoid reaching tasks in dynamic environments
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ECAL
2007
Springer
15 years 3 months ago
Neuroevolution of Agents Capable of Reactive and Deliberative Behaviours in Novel and Dynamic Environments
Both reactive and deliberative qualities are essential for a good action selection mechanism. We present a model that embodies a hybrid of two very different neural network archit...
Edward Robinson, Timothy Ellis, Alastair Channon
NIPS
2001
14 years 11 months ago
Linking Motor Learning to Function Approximation: Learning in an Unlearnable Force Field
Reaching movements require the brain to generate motor commands that rely on an internal model of the task's dynamics. Here we consider the errors that subjects make early in...
O. Donchin, Reza Shadmehr
WOA
2001
14 years 11 months ago
Implementing Adaptive Capabilities on Agents that Act in a Dynamic Environment
Acting in a dynamic environment is a complex task that requires several issues to be investigated, with the aim of controlling the associated search complexity. In this paper, a l...
Giuliano Armano, Giancarlo Cherchi, Eloisa Vargiu
AAAI
2010
14 years 9 months ago
Biped Walk Learning Through Playback and Corrective Demonstration
Developing a robust, flexible, closed-loop walking algorithm for a humanoid robot is a challenging task due to the complex dynamics of the general biped walk. Common analytical ap...
Çetin Meriçli, Manuela M. Veloso
AAAI
2007
14 years 12 months ago
Adaptive Localization in a Dynamic WiFi Environment through Multi-view Learning
Accurately locating users in a wireless environment is an important task for many pervasive computing and AI applications, such as activity recognition. In a WiFi environment, a m...
Sinno Jialin Pan, James T. Kwok, Qiang Yang, Jeffr...