Questions tagged [model-based-methods]

For questions about model-based reinforcement learning methods (or algorithms). An example of a model-based algorithm is Dyna-Q, which estimates a model of the environment (i.e. the transition function of the associated Markov decision process).

10 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
5
votes
0answers
69 views

Choosing Machine Learning Algorithm: Learning-Based Testing

This is my first project using machine learning so I'm looking for some guidance. I am extending a model-based testing (MBT) system to a learning-based testing system by integrating a machine learning ...
3
votes
0answers
25 views

Difference between a distribution model and a sampling environment in Reinforcement Learning

The book from Sutton and Barto define a model in Reinforcement Learning as "something that mimics the behavior of the environment, or more generally, that allows inferences to be made about how ...
2
votes
0answers
53 views

Correlating two models to predict the output of one that corresponds to an output of the other

I am currently working on a problem and now got stuck to implement one of it's steps. This is a simple attempt to explain what I am currently facing, which is something that I am aiming to implement ...
2
votes
0answers
70 views

Eligibility trace In Model-based Reinforcement Learning

In model-based reinforcement learning algorithms, the model of the environment is constructed to efficiently use samples, models such as Dyna, and Prioritize Sweeping. Moreover, eligibility trace ...
1
vote
1answer
85 views

Model-based RL for time series data

I have time-series data. When I take an action, it impacts the next state, because my action directly determines the next state, but it is not known what the impact is. To be concrete: I have $X(t)$ ...
1
vote
0answers
68 views

What kind of reinforcement learning method does AlphaGo Deepmind use to beat the best human Go player?

In reinforcement learning, there are model-based versus model-free methods. Within model-based ones, there are policy-based and value-based methods. AlphaGo Deepmind RL model has beaten the best Go ...
1
vote
0answers
51 views

Using a model-based method to build an accurate day trading environment model

There are several different angles we can classify Reinforcement Learning methods from. We can distinguish three main aspects : Value-based and policy-based On-policy and off-policy Model-free and ...
1
vote
0answers
24 views

Architecture and Use of Different Algorithms for Health Goal Feedback

I wanted to get some opinions from the community for a certain problem that I will be approaching. The problem is to provide feedback to a user based on a image of the upper male torso. The image ...
0
votes
0answers
13 views

Why has PILCO not been included in Sutton & Barto?

PILCO is a model-based Reinforcement Learning method introduced in 2011 by Deisenroth and Rasmussen. As far as I know, it is still considered one of the most important RL method, especially for its ...
0
votes
0answers
19 views

Using an LSTM for model-based RL in a POMDP

I am trying to set up an experiment where an agent is exploring an n x n gridworld environment, of which the agent can see some fraction at any given time step. I'd like the agent to build up some ...