The Bayesian committee machine (BCM) is a novel approach to combining estimators which were trained on different data sets. Although the BCM can be applied to the combination of a...
Creating artificial life forms through evolutionary robotics faces a “chicken and egg” problem: learning to control a complex body is dominated by problems specific to its s...
Image content analysis has become an important issue in multimedia processing. Region-based image retrieval systems attempt to reduce the gap between high-level semantics and low-l...
We study decision-theoretic planning or reinforcement learning in the presence of traps such as steep slopes for outdoor robots or staircases for indoor robots. In this case, achi...
The number of required hidden units is statistically estimated for feedforward neural networks that are constructed by adding hidden units one by one. The output error decreases w...