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» Explanation-Based Neural Network Learning for Robot Control
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ECAL
2001
Springer
15 years 6 months ago
Evolution of Reinforcement Learning in Uncertain Environments: Emergence of Risk-Aversion and Matching
Reinforcement learning (RL) is a fundamental process by which organisms learn to achieve a goal from interactions with the environment. Using Artificial Life techniques we derive ...
Yael Niv, Daphna Joel, Isaac Meilijson, Eytan Rupp...
96
Voted
ECAL
2007
Springer
15 years 8 months ago
Neural Uncertainty and Sensorimotor Robustness
Real organisms live in a world full of uncertain situations and have evolved cognitive mechanisms to cope with problems based on actions and perceptions which are not always reliab...
Jose A. Fernandez-Leon, Ezequiel A. Di Paolo
123
Voted
JMLR
2002
133views more  JMLR 2002»
15 years 1 months ago
Learning Precise Timing with LSTM Recurrent Networks
The temporal distance between events conveys information essential for numerous sequential tasks such as motor control and rhythm detection. While Hidden Markov Models tend to ign...
Felix A. Gers, Nicol N. Schraudolph, Jürgen S...
147
Voted
ASIAMS
2008
IEEE
15 years 8 months ago
HiNFRA: Hierarchical Neuro-Fuzzy Learning for Online Risk Assessment
Our previous research illustrated the design of fuzzy logic based online risk assessment for Distributed Intrusion Prediction and Prevention Systems (DIPPS) [3]. Based on the DIPP...
Kjetil Haslum, Ajith Abraham, Svein J. Knapskog
119
Voted
ICRA
2008
IEEE
208views Robotics» more  ICRA 2008»
15 years 8 months ago
Unsupervised body scheme learning through self-perception
— In this paper, we present an approach allowing a robot to learn a generative model of its own physical body from scratch using self-perception with a single monocular camera. O...
Jürgen Sturm, Christian Plagemann, Wolfram Bu...