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The Lateral Superior Olive (LSO) codes for interaural intensity difference (IID), a cue used for sound localization. Between birth and maturation, the LSO undergoes plasticity driven by input neurons activity. During this developmental phase, a number of inputs are pruned out leading to a refinement of the frequency tuning. The goal of this paper is to show that, using a physiologically plausible...
We have developed a new reinforcement learning (RL) technique called Bayesian-discrimination-function-based reinforcement learning (BRL). BRL is unique, in that it does not have state and action spaces designed by a human designer, but adaptively segments them through the learning process. Compared to other standard RL algorithms, BRL has been proven to be more effective in handling problems encountered...
This paper introduces a novel multi-cellular developmental system where cells are placed in a continuous space. Cells communicate by diffusing and perceiving substances in the environment and are able to migrate around following affinities with substance gradients. The optimization process is performed using Echo State neural networks on the problem of minimizing tile size variations in the context...
The purpose of this paper is to outline a new formulation of statistical learning that will be more useful and relevant to the field of robotics. The primary motivation for this new perspective is the mismatch between the form of data assumed by current statistical learning algorithms, and the form of data that is actually generated by robotic systems. Specifically, robotic systems generate a vast...
It has been shown recently that dopamine signalled modulation of spike timing-dependent synaptic plasticity (DA-STDP) can enable reinforcement learning of delayed stimulus-reward associations when both stimulus and reward are delivered at precisely timed intervals. Here, we test whether a similar model can support learning in an embodied context, in which timing of both sensory input and delivery...
Both self-learning architecture (embedded structure) and explicit/implicit teaching from other agents (environmental design issue) are necessary not only for one behavior learning but more seriously for life-time behavior learning. This paper presents a method for a robot to understand unfamiliar behavior shown by others through the collaboration between behavior acquisition and recognition of observed...
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