SIGNAL NEUTRALITY, SCALAR PROPERTY, AND COLLAPSING BOUNDARIES AS CONSEQUENCES OF A LEARNED MULTI-TIMESCALE STRATEGY.

Signal neutrality, scalar property, and collapsing boundaries as consequences of a learned multi-timescale strategy.

We postulate that three fundamental elements underlie a decision making process: perception of time passing, information processing in multiple timescales and reward maximisation.We build a simple reinforcement learning agent upon these principles that we train on a random dot-like task.Our results, similar to the experimental data, demonstrate thr

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