Questions tagged [double-dqn]

For questions about the double DQN model introduced in the paper "Deep Reinforcement Learning with Double Q-learning" (2015) by Hado van Hasselt et al.

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How should I model the state and action spaces for a problem where the goal is to draw a line between two points?

I have a problem where the goal is for the agent to draw a single line between two points on a $500 \times 500$ white image. I have built my DQN. For now, the output layer's size of the network is $[...
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166 views

Why does regular Q-learning (and DQN) overestimate the Q values?

The motivation for the introduction of double DQN (and double Q-learning) is that the regular Q-learning (or DQN) can overestimate the Q value, but is there a brief explanation as to why it is ...
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Can DQN outperform DoubleDQN?

I found a similar post about this issue, but unfortunately I did not find a proper answer. Are there any references where DQN is better than DoubleDQN, that is DoubleDQN does not improve DQN ?
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DDQN Agent in Othello (Reversi) game struggle to learn

This is my first question on this forum and I would like to welcome everyone. I am trying to implement DDQN Agent playing Othello (Reversi) game. I have tried multiple things but the agent which seems ...
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16 views

Would it make sense to share the layers (except the last one) of the neural networks in Double DQN?

Context: Double Q-learning was introduced to prevent the maximization bias from q-learning. Instead of learning a single Q-network, we can learn two (or in general $K > 1$) and our Q-estimate would ...
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21 views

DQN rgb input channels problem using pytorch

I've been trying to learn about CNN's and reinforcement learning and I found this project to play with: https://github.com/adityajn105/flappy-bird-deep-q-learning I've been trying to change the code ...
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62 views

Why do we minimise the loss between the target Q values and 'local' Q values?

I have a question regarding the loss function of target networks and current (online) networks. I understand the action value function. What I am unsure about is why we seek to minimise the loss ...
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93 views

How to compute the target for double Q-learning update step?

I've already read the original paper about double DQN but I do not find a clear and practical explanation of how the target $y$ is computed, so here's how I interpreted the method (let's say I have 3 ...
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263 views

What exactly is the advantage of double DQN over DQN?

I started looking into the double DQN (DDQN). Apparently, the difference between DDQN and DQN is that in DDQN we use the main value network for action selection and the target network for outputting ...
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106 views

How does the target network in double DQNs find the maximum Q value for each action?

I understand the fact that the neural network is used to take the states as inputs and it outputs the Q-value for state-action pairs. However, in order to compute this and update its weights, we need ...
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76 views

Why does adding another network help in double DQN? [duplicate]

What is the idea behind double DQN? The target in double DQN is computed as follows $$ Y_{t}^{\text {DoubleQ }} \equiv R_{t+1}+\gamma Q\left(S_{t+1}, \underset{a}{\operatorname{argmax}} Q\left(S_{t+1},...
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209 views

How to choose hyperparameters in double DQN?

I'm looking for some indications about the tuning of hyper-parameters in building my double DQN. I have a time series problem (with about 2000 observations and no terminal state, I have to max the ...
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88 views

What does the notation $p_t = \text{max}_{i<t} p_i$ mean in algorithm 1 of the prioritized experience replay paper?

I am having a hard time converting line 6 of the prioritized experience replay algorithm from the original paper into plain English (see below): I understand that new transitions (not visited before) ...
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457 views

Can DQN perform better than Double DQN?

I'm training both DQN and double DQN in the same environment, but DQN performs significantly better than double DQN. As I've seen in the double DQN paper, double DQN should perform better than DQN. Am ...