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Questions tagged [dqn]

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RL library for implementing PPO algorithm

I have recently studied about PPO algorithm. I want to train an RL agent using PPO. However I am finding it difficult to implement. So I am planning to use a library which will help me in the ...
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1answer
20 views

Policy Gradient with continuous action space

How to apply reinforce/policy-gradient algorithms for continuous action space. I have learnt that one of the advantages of policy gradients is , it is applicable for continuous action space. One way I ...
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0answers
9 views

Major drop in DeepQNetwork agent after certain number of iteration

I've built a game with an agent moving around trying to collect gold (+10 reward) and it dies when it hits a wall (-100, terminal condition) and -1 for any other step that is not gold nor wall. My ...
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1answer
35 views

Deep reinforcement learning on changing data sizes

I have a game that I want to build a model that will learn to play the game. Yet, the environment output is two lists that represent the location and number of soldiers of the user and Opponent. The ...
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2answers
86 views

Agent always takes a same action in DQN - Reinforcement Learning

I have trained an RL agent using DQN algorithm. After 20000 episodes my rewards are converged. Now when I test this agent, the agent is always taking the same action , irrespective of state. I find ...
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9 views

How to calculate Temperature variable in softmax(boltzmann) exploration

Hi I am developing a reinforcement learning agent for a continous state/discrete action space. I am trying to use boltmzann/softmax exploration as action selection strategy. My action space is of size ...
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23 views

Reducing the training time of an RL agent

I am trying to develop an rl agent using DQN algorithm.During training, the agent interacts with environment which is a simulated one.Each episode takes around 10 mins to run. This way if want my ...
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1answer
21 views

How to formulate reward of an rl agent with two objectives

I have started learning reinforcement learning and trying to apply it for my use case. I am developing an rl agent which can maintain temperature at a particular value, and minimize the energy ...
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1answer
21 views

Is DQN limited to working with only image frames?

I have few questions about Deep Q Network. Does DQN only accept image frames as input? I have never hear (read) a paperwork where it doesn't use image frames. If the first is a No, then does image ...
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0answers
27 views

How can I improve the performance of my DQN?

I created a deep Q network to play snake. The code works fine, except for the fact that performance doesn't really improve over the training cycle. At the end, it's pretty much indistinguishable from ...
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0answers
24 views

Are convolutional layers necessary for deep Q networks?

I'm currently trying to build a deep Q network to play the classic Snake game. I designed the game in such a way that the state space is confined to a 20 x 20 matrix, with 1's representing a square ...
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1answer
40 views

Deep Q-Learning for physical quantity: q-values distribution not as expected

Setting I am trying to learn a specific physical quantity (radiance) inside a 3D scene with Deep Q-Learning. Just to give a quick overview, my agent shoots rays inside the scene: the reward is the ...
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15 views

Why does calling model.fit() with a batch result in much worse results than calling it individually with each item?

I've been trying to track down poor performance of a DQN playing CartPole. I compared it to another sample online that performed much better and slowly worked through every difference, isolating the ...
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20 views

DQNs for huge or continuous state spaces

Have there been occasions where DQN failed to deal with huge state spaces? Can you point out a research paper regarding it?
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1answer
178 views

Difference between Dueling DQN and Double DQN?

I have read some articles, but still can not figure out the difference between the Dueling DQN and Double DQN? What exactly is the difference between them? Also, Does Dueling DQN need to be built on ...
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63 views

How to train DDQN model in reinforcement learning?

I was reading through some RL code but couldn't understand one small bit. here is the code: ...
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17 views

Fetch (multi joint robot) DQN training: How to do action selection?

I am implementing a DQN using a similar environment to OpenAI fetch envs. I am trying to convert them to pybullet implementations. When training a DQN for a multi-joint robot like the Fetch, ...
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1answer
74 views

How does DQN solve Open AI Cartpole - v0?

Context I am confused about how a DQN is supposed to solve the cart pole problem since the rewards are so dense. I have been using pytorch example. I am aware of some solutions, but I have issue with ...
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1answer
175 views

Q-Learning experience replay: how to feed the neural network?

I'm trying to replicate the DQN Atari experiment. Actually my DQN isn't performing well; checking another one's codes, I saw something about experience replay which I don't understand. First, when you ...
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1answer
305 views

DQN fails to find optimal policy

Based on DeepMind publication, I've recreated the environment and I am trying to make the DQN find and converge to an optimal policy. The task of an agent is to learn how to sustainably collect apples ...
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0answers
14 views

Is reward accumulated during a play iteration when performing SARSA?

I've been having issue with getting my DQN to converge to a good solution for snake. Regardless of the different types of reward functions I've tried, it seems that the snake is indefinitely going ...
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15 views

Is DQN independent from type of input distribution?Why?

Can we say: Since DQN is online learning, it is independent of type of input distribution?
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0answers
283 views

Deep Reinforcement Learning for dynamic pricing

I am trying to implement a Deep Q Network model for Dynamic pricing in Logistics. I can define State Space (Origin, Destination, type of the shipment, customer, Type of the product, Commodity of the ...
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1answer
189 views

how to choose between discounted reward and average reward

how to select between average reward and discounted reward? And when average reward is more effective in comparison with discounter reward and when vice versa is correct? -Is is possible to use both ...
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16 views

Is DQN a SMART (Semi Markov Average Reward Technique)?

Is DQN a SMART (Semi Markov Average Reward Technique) algorithm?
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24 views

What is the meaning of the Variant Q-learning and To what INPUT and OUTPUT refer? in Abstract of DeepMind DQN paper 2013

-INPUT and OUTPUT OF ATARI DQN: In the abstract paragraph of the DQN work by DeepMind https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf it has written: " We present the first deep learning model to ...
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6 views

effects of number of running time periods on examining the DQN quality?

What are the effects of the number of running time periods on examining the DQN quality? I mean "T": time periods of training and testing. If there is not an obligation to set it to a value in the ...
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1answer
523 views

RL - Weighthing negative rewards [closed]

Let's consider that I give an agent a reward of -1 (minimum reward) every time it performs an action which leads to the premature end of the episode (i.e., the agent dies). Besides, I also give a ...
4
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1answer
709 views

How does Implicit Quantile-Regression Network (IQN) differ from QR-DQN?

For several months I browsed the internet hoping to find a user-friendly explanation of the Implicit Quantile Regression Network (IQN). But, it seems there is none at all. How does IQN differ from ...
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1answer
49 views

Will reinforcement learning work if states wont get repeated again?

I am working on a information retrieval model where the user enters a query and the model has to retrieve 3 most relevant FAQ pairs.I am collecting implicit feedback in terms of page clicks etc.What I ...
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0answers
103 views

comparison of linear Q-learning and DQN

I saw in DQN nature paper 2015 https://www.nature.com/articles/nature14236(Extended Data Table 4) some comparisons between DQN and linear Q-learning. The ratio ...
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1answer
138 views

is it acceptable if the reward of test of DQN is lower than reward of training of DQN in minimization problem?

if we train a DQN over 40000-60000 episodes for 500 time steps. The mean of reward during last 100 training steps is about 1.1 times of reward during the test process. Environment is stochastic! The ...
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1answer
50 views

“Each agent was evaluated every 250,000 training frames for 135,000 validation frames” What does this sentences stands for? in DQN nature paper?

In nature paper of DQN by DeepMind, DQN is compared to linear function but they does not said what is this linear function? They compared with some linear functions? 0- What is the meaning of this ...
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1answer
356 views

How to implement clipping the reward in DQN in keras

How to implement clipping the reward in DQN in keras? especially how to implement clipping the reward? Is this pseudo code correct: ...
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1answer
286 views

What are the effects of clipping the reward in stability?

I am looking for stabilizing my results of DQN, I found clipping is one technique to do it but I did not understand it completely! 1- what are the effects of clipping the reward, clipping the ...
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1answer
100 views

What is difference between final episodes of training and test in DQN?

What is difference between running in final episode of training mode and running in test mode in DQN? Is there any difference more than after training and tune the hyper-parameters, we test for one ...
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0answers
394 views

DQN cannot learn or converge

I have implemented a DQN using keras. The task is to collect the circles and avoid the red circle and crosses. The associated rewards are +5, -5 and 0 otherwise. if the agent go out of the board, the ...
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2answers
3k views

what is difference between the DDQN and DQN?

I think I did not understand what is the difference between DQN and DDQN in implementation. I understand that we change the traget network during the running of DDQN but I do not understand how it is ...
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3answers
53 views

Which is more important - stable training results or good test results?

Which is more important - stable training results or good test results? For instance, is obtaining an unstable training accuracy in different epochs, but good test accuracy better? Or is obtaining a ...
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0answers
124 views

How to resolve the instability of average reward per episode in training of DQN (Deep Q-Network)?

what is shown when average reward per episode in training is unstable? If there is big difference between average reward per episode and final reward by test section, what we can say? For ...
2
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1answer
170 views

Why does exploration in DQN not lead to instability?

Why does action exploration in DQN not lead to instability? I see in DQN algorithms, that it selects random actions even after some iterations. My question is how does this approach not lead to ...
2
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1answer
61 views

How we can have RF-QLearning or SVR-QLearning (Combine these algorithm with a Q-Learning )

How we can have RF-QLearning or SVR-QLearning (Combine these algorithm with a Q-Learning )? I want to replace the DNN section of Qlearning with a RF or SVR but the problem is that there is no clear ...
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1answer
99 views

Is the neural network in DQN used to learn like a supervised model?

Is the neural network in DQN used to learn like a supervised model?
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0answers
503 views

Why is my loss function for DQN converging too quickly?

I'm still relatively new to deep learning and am experiencing an issue that I can't seem to find a solution/explanation for. I've developed a DQN model in tensorflow, as described by DeepMind, and am ...
2
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1answer
139 views

What is wrong with this reinforcement learning environment ?

I'm working on below reinforcement learning problem: I have bottle of fix capacity (say 5 liters). At the bottom of bottle there is cock to remove water. The distribution of removal of water is not ...
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1answer
268 views

How to give rewards to actions in RL?

I'm working on below reinforcement learning problem: I have bottle of fix capacity (say 5 liters). At the bottom of bottle there is cock to remove water. The distribution of removal of water is not ...
1
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0answers
168 views

Deep Q-Learning with large number of actions

I'm using DQN with large number of actions in [0, 10000, step = 1000]. This means I have an action space of size 11 (including 0 and 10000). Action space is still discrete. My problem is that, instead ...
3
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1answer
288 views

Difference between advantages of Experience Replay in DQN2013 paper

I've been re-reading the Playing Atari with Deep Reinforcement Learning (2013) paper. It lists three advantages of experience replay: This approach has several advantages over standard online Q-...
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1answer
395 views

Why is Distributional DQN faster than vanilla DQN?

Recently I learned about Distributional approach to RL, which is a quite fascinating and break--through algorithm. I have 2 questions: What is it that makes it perform so much better during runtime ...
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0answers
36 views

Can a DQN output a float result? [closed]

I'm a newbie of Deep Q Learning. After read some papers and tutorials on the web, I tried to train a DQN to control a game using TensorFlow. The input is the screenshoot of the game. The output is an ...