Signal neutrality, scalar property, and collapsing boundaries as consequences of a learned multi-timescale strategy.
We postulate that three neflintw-r6mpw 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,