[–] mrdrozdov 9y ago ↗ Always useful to see implementations of simple components, like epsilon greedy action choice: function nql:eGreedy(state, testing_ep) self.ep = testing_ep or (self.ep_end + math.max(0, (self.ep_start - self.ep_end) * (self.ep_endt - math.max(0, self.numSteps - self.learn_start))/self.ep_endt)) -- Epsilon greedy if torch.uniform() < self.ep then return torch.random(1, self.n_actions) else return self:greedy(state) end end
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