具有自主动力学的认知系统中的学习
Learning in cognitive systems with autonomous dynamics
摘要：
像人脑这样高度发达的认知系统的活动模式是由自主的动力学过程主导的，也就是说，由一种自我维持的活动主导，这种活动即使在没有外部感官刺激的情况下也会存在。因此，在正常操作期间，外部刺激的持续流入可能与自主动力过程内部产生的模式完全无关。因此，需要避免学习外部刺激和自主产生的内部活动状态之间的虚假相关性。我们研究这个问题的内部活动的瞬态动力学的范式内，这是一个自治的活动，其特征在于由一个无限的时间序列的瞬态稳定的吸引子状态。我们建议，外部刺激将是相关的敏感期，过渡期之间的一个瞬态和随后的半稳定吸引子。每当刺激定性地影响内部动态时，无监督地生成扩散学习信号。为了测试，我们已经提出了相应的酒吧条纹问题的模型系统的刺激，并发现它能够执行所需的独立分量分析自己，所有的时间都是连续和自主的活动。
英文摘要：
The activity patterns of highly developed cognitive systems like the human brain are dominated by autonomous dynamical processes, that is by a self-sustained activity which would be present even in the absence of external sensory stimuli. During normal operation the continuous influx of external stimuli could therefore be completely unrelated to the patterns generated internally by the autonomous dynamical process. Learning of spurious correlations between external stimuli and autonomously generated internal activity states needs therefore to be avoided. We study this problem within the paradigm of transient state dynamics for the internal activity, that is for an autonomous activity characterized by a infinite time-series of transiently stable attractor states. We propose that external stimuli will be relevant during the sensitive periods, the transition period between one transient state and the subsequent semi-stable attractor. A diffusive learning signal is generated unsupervised whenever the stimulus influences the internal dynamics qualitatively. For testing we have presented to the model system stimuli corresponding to the bar-stripes problem and found it capable to perform the required independent-component analysis on its own, all the time being continuously and autonomously active.
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