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Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail

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Figure

Figure 1. Postsynaptic factors of the learning rule. A model neuronrule evaluated in time steps of 1 ms (see Eq
Figure 2. Hippocampal model. A: Schematic overview. Place cellsare connected via all-to-all feedforward connections (red) to the actioncells, which in addition receive lateral input (light blue) via connectionswith a mexican hat profile (not all connection
Figure 3. Learning performance for different variants of thelearning rule.as in Model architecture, Methods and Tables 1, 2.probabilityNavigation map after 20 trials visualized in the water maze by a setof direction vectors
Figure 4. Learning algorithm. The decision timeResults. T can be either 200ms, as in most cases, or can be based on a flexible criterion (Figure 3 C–E), seedoi:10.1371/journal.pcbi.1000586.g004
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