Questions tagged [pomdp]

For questions related to the concept of Partially Observable Markov Decision Process (POMDP), which is a generalization of the Markov Decision Process (MDP) to the cases where information about the states is incomplete (or partially observable).

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37 views

What is the difference between Bayes-adaptive MDP and a Belief-MDP in Reinforcement Learning?

I have been reading a few papers in this area recently and I keep coming across these two terms. As far as I'm aware, Belief-MDPs are when you cast a POMDP as a regular MDP with a continuous state ...
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56 views

If the performance of an RL agent in a partially observable environment is “good”, is this likely only accidental?

In my research, I remember to have read that, in case of an environment which can be modeled by partially observable MDP, there are no convergence guarantees (unfortunately, I do not find the paper ...
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2answers
45 views

Does “transition model” alone in an MDP imply it's non-deterministic?

I am looking at a lecture on POMDP, and the context is that, when the quadcopter can't see the landmarks, it has to use reckoning. And then he mentions the transition model is not deterministic, hence ...
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How to choose an RL algorithm for a Gridworld that models a much more complex problem

I am considering using Reinforcement Learning to do optimal control of a complex process that is controlled by two parameters $(n_O, n_I), \quad n_I = 1,2,3,\dots, M_I, n_O = 1,2,3,\dots, M_O$ In this ...
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0answers
59 views

Can we use a Gaussian process to approximate the belief distribution at every instant in a POMDP?

Suppose $x_{t+1} \sim \mathbb{P}(\cdot | x_t, a_t)$ denotes the state transition dynamics in a reinforcement learning (RL) problem. Let $y_{t+1} = \mathbb{P}(\cdot | x_{t+1})$ denote the noisy ...
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33 views

Is Monte Carlo tree search needed in partially observable environments during gameplay?

I understand that with a fully observable environment (chess / go etc) you can run an MCTS with an optimal policy network for future planning purposes. This will allow you to pick actions for gameplay,...
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1answer
56 views

What is the intuition behind grid-based solutions to POMDPs?

After spending some time reading about POMDP, I'm still having a hard time understanding how grid-based solutions work. I understand the finite horizon brute-force solution, where you have your ...
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35 views

Why can the core reinforcement learning algorithms be applied to POMDPs?

Why can an AI, like AlphaStar, work in StarCraft, although the environment is only partially observable? As far as I know, there are no theoretical results on RL in the POMDP environment, but it ...
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44 views

How exactly does self-play work, and how does it relate to MCTS?

I am working towards using RL to create an AI for a two-player, hidden-information, a turn-based board game. I have just finished David Silver's RL course and Denny Britz's coding exercises, and so am ...
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25 views

What are some approaches to estimate the transition and observation probabilities in POMDP?

What are some common approaches to estimate the transition or observation probabilities, when the probabilities are not exactly known? When realizing a POMDP model, the state model needs additional ...
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0answers
21 views

Finding total number of states in a POMDP

I've been working on a question that is posed in a document I've been reading, that models qualifying for a job as a POMDP. In this model, a person takes 3 exams, and must pass all of them in order to ...
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78 views

Is there a way to do reinforcement learning in POMDP?

Are there any algorithms to use reinforcement learning to learn optimal policies in partially observable Markov decision process (POMDP) i.e. when the state is not perfectly observed. More ...
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1answer
1k views

Can Q-learning be used in a POMDP?

Can Q-learning (and SARSA) be directly used in a Partially Observable Markov Decision Process (POMDP)? If not, why not? My intuition is that the policies learned will be terrible because of partial ...
2
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1answer
43 views

Can the normalization factor for the belief state update be zero?

In order to update the belief state in a POMDP, the following formula is used: $$b'(s')=\frac{O(a, s', z) \sum_{s\in S} b(s)T(s, a, s')}{\mathbb{P}(z \mid b, a)}$$ where $s$ is a specific state in ...
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1answer
70 views

Does the observation function for POMDP always add up to 1?

I was reading in the article A tutorial on partially observable Markov decision processes (p. 120), by Michael L. Littman, that $\sum_{z \in Z}O(a, s',z) =1$, where $a$ is the action, $s'$ the next ...
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1answer
93 views

What is the appropriate approach to playing a game with incomplete state information?

I have a steady hex-map and turn-based war game featuring WWII carrier battles. I would like to improve the fixed policy for the AI using reinforcement learning. I have some beginner's questions, ...
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534 views

Is my understanding of the differences between MDP, Semi MDP and POMDP correct?

I just wanted to confirm that my understanding of the different Markov Decision Processes are correct, because they are the fundamentals of reinforcement learning. Also, I read a few literature ...
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2answers
104 views

How to define reward function in POMDPs?

How do I define a reward function for my POMDP model? In the literature, it is common to use one simple number as a reward, but I am not sure if this is really how you define a function. Because this ...