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Questions tagged [environment]

For questions related to the concept of environment in reinforcement learning and other AI sub-fields.

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5 votes
1 answer
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Why is it recommended to use a "separate test environment" when evaluating a model?

I am training an agent (stable baselines3 algorithm) on a custom environment. During training, I want to have a callback so that for every $N$ steps of the learning process, I get the current model ...
jgklsdjfgkldsfaSDF's user avatar
4 votes
2 answers
155 views

How to represent players in a multi agent environment so each model can distinguish its own player

So I have 2 models trained with the DQN algorithm that I want to train in a multi-agent environment to see how they react with each other. The models were trained in an environment consisting of 0's ...
Milky's user avatar
  • 41
3 votes
1 answer
95 views

What are the strategies for computationally heavy environments or long-time waiting environments?

I have an environment that is computationally heavy (takes several seconds to get a reward and next state). This limits reinforcement capability, due to poor sampling of the problem. There is any ...
Daniel Wiczew's user avatar
2 votes
0 answers
171 views

What to look out for when designing an environment regarding observations?

When designing an environment, what should one look out for when designing the observation space to make the environment as easy to be learnable for an agent as possible? E.g. make sure the markov ...
kitaird's user avatar
  • 115
2 votes
0 answers
91 views

What is the appropriate way of passing a list of integers that represents the environment to a neural network's dense layer?

I'm training an RL agent using the DQN algorithm to do a specific task. The environment is represented by a list of $10$ integer numbers from $0$ to $20$. An example would be $[5, 15, 8, 8, 0, \dots]$....
mark mark's user avatar
  • 773
2 votes
0 answers
84 views

Should the RL agent be trained in an environment with real-world data or with a synthetic model?

I want to train a reinforcement learning agent in an environment with parameters (for example, the wind speed, sun irradiation, etc.) that change over time. I have recorded a limited amount of data ...
flxh's user avatar
  • 131
1 vote
0 answers
78 views

How many parameters of a RL environment?

I’m working at a Reinforcement Learning model, using PPO algorithm, in which the agent has 4 possible actions, acting in a stochastic environment defined by 3 parameters. Given its stochasticity, I ...
Damuna Taliffato's user avatar
1 vote
0 answers
148 views

Is object-based representation of the observation space feasible?

I just started working on a DRL project from scratch. The state of each episode can be expressed as a state set $S=(S^A, S^B, S^C, S^D)$. Each subset is a feature set of a constituent component of the ...
Shahin's user avatar
  • 153
1 vote
0 answers
34 views

What if the rewards induced by an environment are related to the policy too?

Assume we have a policy $\pi_{\theta}$ in a classic reinforcement learning setting, and a reward function $R^{\pi}(s,a)$ that changes as long as $\pi$ changes i.e. not only is it predefined by the ...
ASA's user avatar
  • 151
1 vote
0 answers
56 views

Why does this tutorial on reinforced learning not check whether the environment is 'game over' during training?

I am following the tutorial Train a Deep Q Network with TF-Agents. It uses the hello world environment of reinforced learning: cart pole. At the end, the agent is ...
Mike de Klerk's user avatar
1 vote
0 answers
215 views

How do I know if the assumption of a static environment is made?

An important property of a reinforcement learning problem is whether the environment of the agent is static, which means that nothing changes if the agent remains inactive. Different learning methods ...
maven's user avatar
  • 31
1 vote
0 answers
91 views

What are a list of board game environments for RL practice?

Recently OpenAI removes their board game environments. (It may be possible to install an older version to get access to them, but I haven’t downgraded). Is there a list of repositories or resources ...
Hanzy's user avatar
  • 519
0 votes
0 answers
19 views

When should grayscale processing be applied to image inputs in visual reinforcement learning environments?

I am currently working with visual environments in Reinforcement Learning (RL) and have noticed differing practices regarding preprocessing of image inputs. Specifically, in the Atari environment, a ...
XiaoBanni's user avatar
0 votes
0 answers
99 views

Which algorithms work in a non-stationary stochastic environment?

Currently, I am reading into the Multi-Armed-Bandit problem and found the special case of non-stationary (environment and its attributes, like the reward distribution, change over time) stochastic ...
paperplan3's user avatar
0 votes
0 answers
121 views

Strange behavior of Q-learning agent after being trained

I built a simple X*Y grid world environment to learn and then trained my agent over it. All worked fine and the agent learned as well. Let me give some detail about the environment. Environment: A ...
SJa's user avatar
  • 393
0 votes
1 answer
72 views

How to let the agent choose how to populate a state space matrix in RL (using python)

I have an agent (drone) that has to allocate subchannels for different types of User Equipment. I have represented the subchannel allocation with a 2-dimentional binary matrix, that is initialized to ...
Ness's user avatar
  • 206