Authors: Dimiter Dobrev
In Reinforcement Learning we look for a model of the world. Typically, we aim to find a model which tells everything or almost everything. In other words, we hunt for a perfect model (a total determinate graph) or for an exhaustive model (Markov Decision Process). Finding such a model is an overly ambitious task and indeed a practically unsolvable problem with complex worlds. In order to solve the problem, we will replace perfect and exhaustive models with Event-Driven models.
Comments: 1 Page. This is a short summary.
[v1] 2019-02-15 04:35:12
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