Questions tagged [markov-chains]

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information theory, find entropy given Markov chain

There is an information source on the information source alphabet $A = \{a, b, c\}$ represented by the state transition diagram below: a) The random variable representing the $i$-th output from this ...
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12 views

Logical inference as Markov decision process?

Are there efforts to consider forward or backward (theorem proving) logical inference process as Markov decision process in which the the action space is: 1) selection of the inference rule (e.g. from ...
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1answer
25 views

How to find optimal token set for compression?

By token I mean the smallest element of source data, that the compression algorithm works on. It may be a bit (like in DMC), a letter (like in Huffman or PPM), a word, or variable-length string (like ...
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1answer
23 views

Probabilisitc timed automaton

I am kind of new to timed automaton domain. I am trying to understand in which way they are different to Markov Decision Process. First I know there objectives is to solve the non-determinism of a MDP....
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1answer
37 views

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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1answer
31 views

Sampling Multiple Times From a Markov Chain

In probability theory, the mixing time of a Markov chain is the time until the Markov chain is "close" to its steady state distribution. Lets fix some $\varepsilon\in (0,1]$ as our closeness parameter....
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1answer
452 views

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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0answers
36 views

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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53 views

The relationship between MDP's end component and its induced MC recurrent class

Let's assume that I have an MDP $M$ which has a number of maximal end components. I also have a random policy (scheduler) $\pi$ that can convert the MDP $M$ into a Markov chain $m$. Can I argue that ...
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57 views

Game with Random Digits (Markov Chain / Coupling)

I've been self-studying Markov Chains and came across a problem online here: http://websites.math.leidenuniv.nl/probability/lecturenotes/CouplingLectures.pdf I'm not asking for anything too formal (I'...
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1answer
255 views

Why in simulated annealing, thermal equilibrium need to be meet for each temperature throughout the iterations?

I have read in this book, simulated annealing, on page 40-41, if temperature $t$ tend to $0$, then the stationary distribution will be distributed among optimal solutions. What i can not understand ...
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3answers
411 views

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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0answers
106 views

Second-order Markov text generation?

Looking at this video starting at 1:45, the author claims to be using a second-order approximation for a Markov text generation. He has one letter which he outputs followed by another letter which ...
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1answer
51 views

Maximize entrywise 1-norm of matrix product

I have $8$ sets $E_1, \ldots, E_8$, each one of size $256$, whose elements are $4\times 4$ matrices of (nonnegative) integers. I'd like to design an algorithm to find: $$\underset{M_1 \in E_1, \...
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0answers
73 views

Solving the following recurrence relation derived from a Markov chain

I have the following system of recursive relations on $y_{i,j}$ that are derived from a Markov chain and that I am having difficulty in solving. For $i\ge 1$ and $j \ge 1$, we have $$y_{i,j} \times (...
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1answer
664 views

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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54 views

Form of conditional observation probabilities in a POMDP

Consider a partially observable Markov decision process (POMDP), see here for a complete definition. My question is in relation to the conditional observation probabilities (denoted by $O(o|s',a)$ in ...
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89 views

Calculate expected values of “Craps Game” with the help of Prism Model Checker

I have modelled the craps game (https://en.wikipedia.org/wiki/Craps#Rules_of_play) as a dtmc with the prism model checker: ...
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1answer
265 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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155 views

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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0answers
49 views

Calssifying the Partitions of the problem Cycle Decomposition of Markov Chains

The book Cycle Representations of Markov Processes solves the problem of Mapping Stochastic Matrices induced from a Markov Chain into Partitions using a $\lambda$-preserving ($\lambda$ is a Lebesgue ...
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171 views

How the conditional random fields algorithm work? [closed]

Im searching about conditional random fields for a long time and cant understand the concepts of this algorithm. I understood markov chains, and understood that conditional random field is a more ...
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161 views

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,...
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2answers
404 views

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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1answer
90 views

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 ...
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1answer
399 views

Markov Chain Mixing Time of the Complete Graph

I'm having a hard time understanding mixing time for Markov Chains on Complete Graphs (Kn). We can define the probability matrix for Kn where Pi,j=probability of going from i to j (technically 1/...
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1answer
97 views

Clarification of the definition of a POMDP

From what I understand, a $MDP=(G, A, P, R)$ (markov decision process) is represented as: A complete directed graph $G=(V, E)$ A set of actions $A_u$ for each vertex $u \in V$ A reward function $R$ ...
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0answers
149 views

Cheeger constant of a graph versus conductance of a Markov chain

Given some graph $G$ with vertices $V$ and edges $E$, its Cheeger constant $h(G)$ is well defined as $$ h(G) = \min_{S\subset V,0<|S|\leq|V|}\frac{|\partial S|}{|S|}. $$ Given some doubly-...
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236 views

Can the solution to a POMDP be found using linear programming?

It is known that Markov decision processes (MDPs) can be solved using linear programming (see page 24 of Carlos Guestrin's PhD dissertation). The linear program is: $$min_{V(x)} \sum_x \alpha(x)V(x)\\...
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0answers
153 views

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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1answer
75 views

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 ...
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2answers
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 ...
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0answers
37 views

Calibrating a Markov Chain with little data

I am trying to calibrate a Markov Chain. Usually you would have the amount that "moves" from one state to the other and then the resulting value, with data at any given time with the following ...
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0answers
30 views

Mixing time of three particle systems

Is there anything known about mixing time of Markov chains for three particle systems? It is proved here http://www.ams.org/journals/tran/2005-357-08/S0002-9947-05-03610-X/S0002-9947-05-03610-X.pdf ...
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1answer
117 views

Average vs Worst-Case Hitting Time

Consider a simple random walk on an undirected graph and let $H_{ij}$ be the hitting time from $i$ to $j$. How much bigger can $$ H_{\rm max} = \max_{i,j} H_{ij}, $$ be compared to $$ H_{\rm ave} = \...
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1answer
110 views

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. ...
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0answers
85 views

What is the meaning of the output weights of a Conditional Random Field (CRF) model?

Problem When train my linear chain CRF with annotated observations, I feed it with a number of sequences containing observation values and a "ground-truth" label for each observation. I'm currently ...
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0answers
49 views

Graph Centrality: spectral techniques

What is the difference between: normalizing the row of an adjacency matrix and taking the right eigenvector normalizing the row of an adjacency matrix and taking the left eigenvector normalizing the ...
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2answers
3k views

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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1answer
281 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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2answers
212 views

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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1answer
2k views

Algorithm for finding best combination of elements

Say I have a very large, arbitrary number of variables, each of which I can assign to be type A, B, or C. The types come with expenses: Type A's are the least expensive, and C's are the most ...
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363 views

PageRank and EigenTrust: How small should epsilon be?

For probabilistic algorithms such as PageRank and EigenTrust, the stopping case is given as $|R_{t+1} - R_{t}| < \epsilon$ (i.e. convergence is assumed). Neither the papers on EigenTrust or ...
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1answer
414 views

How are Bayesian Nets, Hidden Markov Chains, Conditional Random Fields and Neural Nets related?

I am having an AI exam in two weeks, and I am still figuring out certain concepts and ideas, related to Bayesian Nets, Hidden Markov Chains, Conditional Random Fields and Neural Nets (yes it is all ...
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4answers
3k views

What are the uses of Markov Chains in CS? [closed]

We all know that Markov Chains can be used for generating real-looking text (or real-sounding music). I've also heard that Markov Chains has some applications in the image processing, is that true? ...
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1answer
164 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 ...