Questions tagged [markov-chains]

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What are Markov chains?

I'm currently reading some papers about Markov chain lumping and I'm failing to see the difference between a Markov chain and a plain directed weighted graph. For example in the article Optimal state-...
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Why are HMMs appropriate for speech recognition when the problem doesn't seem to satisfy the Markov property

I'm learning about HMMs and their applications and trying to understand their usages. My knowledge is a bit spotty, so please correct any incorrect assumptions I'm making. The specific example I'm ...
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The transition function in a Markov decision process

A Markov decision process is typically described as a tuple $\langle A,U,T,R \rangle$ where $A$ is the state space $U$ is the action space $T: A \times U \times A \mapsto [0,\infty)$ is the state ...
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Perturbing a Markov chain to be closer to a target stationary distribution

Suppose we are a given a Markov chain $A_0 \in \mathbb{R}^{n \times n}$ and a desired stationary probability vector $\pi_0 \in \mathbb{R}^n$. I would like to find a Markov chain that is as close as ...
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How many possible policies in a Markov Decision Process?

If a policy yields an action for a state, how come a 3-state MDP with 2 possible actions, i.e. $S = \{Hot, Mild, Cold\}$, $A = \{East, West\}$, has 8 possible policies? Isn't it 6 if there are 2 ...
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Seemingly non sequitur in proof

I'm trying to understand a small proof in an article about computing lumpability on Markov chains. There is a small detail that I cannot understand, i.e. I don't think it follows from the argument. ...
167 views

Improve Markov Chain results

Apologies for another Markov Chain question but this one is best given its own question to avoid confusion. I am using a Markov Chain to get the 10 best search results from the union of 3 different ...
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Multicommodity flows with minimum congestion: NP-hard?

I have a question related to a paper of Chen, Lovasz and Pak [1]. The paper concerns the construction of the Markov chain with optimal mixing time on an arbitrary graph. They prove the optimal bound (...
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Why do we need Gibbs sampling (and MCMC)?

I just learned about Gibbs Sampling which is an MCMC method. Given a distribution $\pi$, we want to sample an item according to $\pi$. Maybe my alternative suggestion would sound somewhat naive (even ...
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Orderability of Belief States in a POMDP?

Consider a POMDP with integer states $1,2,\ldots,N$, where $N$ is finite. We thus have a complete order over the states. It seems reasonable to think that belief states for this POMDP may be ...
91 views

How to sample random game input that looks similar to human control?

What I would like to do is improve upon projects like 'RNG plays pokemon'. There, a computer produces a random sequence of inputs that are transmitted to an emulator and played in-game. Though this ...
277 views

Convergence of Markov model

I was learning Hidden Markov model, and encountered this theory about convergence of Markov model. For example, consider a weather model, where on a first-day probability of weather being sunny was 0....
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Card Shuffling, Bounding Mixing time using Paths and Flows

I've been struggling with a problem that is very similar to a 2014 question posted here. The question in particular is 3(1) and 3(2). To paraphrase, we are supposed to use paths and an encoding ...
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Absorbing Markov Chains: An efficient algorithmic approach

Following this procedure I have successfully written a program to calculate the probability of ending in a given absorbing state given the initial state. The procedure is as follows: Given the ...
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Simulating continuous time semi-Markov state machine and changing transition probability on the fly

The problem that I'm trying to solve (well, I think that I almost did, but need a review from someone more experienced) is about changing probability of the transition for semi-Markov state machine ...
288 views

Markov Chain w/ non-stochastic matrix

I've come across a problem which at first appeared to be a markov process however the transition matrix of the graph is non-stochastic. That is, the probabilities among edges leaving a node do not sum ...
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probability matrix from digraph adjacency matrix

All I have in hand is a adjacency matrix of a digraph with equal weight on every edge, is there a very simple way to convert this to a state change probability matrix?
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What's the relationship of max-flow-min-cut and Markov Random Fields?

I am trying to follow this paper [1]. There is a relationship between Markov Random Fields (MRF) to max-flow-min-cut. An MRF can be represented as an undirected graph, and you can find flow through it,...