What is the Probability of Reaching Node D Before Node E Starting from Node G?

In summary: You need to keep your probabilities on a tighter rein... the total allocation of possible events should still only be 1
  • #1
scriby
7
0
http://img844.imageshack.us/img844/8333/1111jx.png

Homework Statement



With which probability, starting in g, node d gets hit before node e?

Homework Equations


The Attempt at a Solution



I think the probability of hitting each node starting in g is the following:

p(g) = 1
p(c) = 1/2
p(a) = 1/3
p(d) = 1
p(b) = 1/3
p(f) = 1
p(e) = 0

Do I just have to add the probabilities from g to d and that's it?
 
Last edited by a moderator:
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  • #2
scriby said:
http://img844.imageshack.us/img844/8333/1111jx.png

Homework Statement



With which probability, starting in g, node d gets hit before node e?


Homework Equations





The Attempt at a Solution



I think the probability of hitting each node starting in g is the following:

p(g) = 1
p(c) = 1/2
p(a) = 1/3
p(d) = 1
p(b) = 1/3
p(f) = 1
p(e) = 0

Do I just have to add the probabilities from g to d and that's it?
Hello scriby. Welcome to PF !

How many choices are there at each node ?
 
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  • #3
SammyS said:
Hello scriby. Welcome to PF !

How many choices are there at each node ?

Hi SammyS , thanks for your reply


g has 1 choice
c has 2 choices
a has 3 choices
d has 1 choice
b has 3 choices
f has 1 choice
e also has 1 choice , but I think since it should not be relevant for the solution we can put it =0 ??
 
  • #4
Starting at g, isn't P(c) = 1 ?
 
  • #5
SammyS said:
Starting at g, isn't P(c) = 1 ?

yes of course...I got a little confused since c has two choices, but yes starting at g there's only one choice and that is c
 
  • #6
On a random walk that terminates on reaching either d or e:

- from g, what is the probability of reaching a?
- from c, what is the probability of reaching a?
- from f, what is the probability of reaching b?
 
Last edited:
  • #7
scriby said:
http://img844.imageshack.us/img844/8333/1111jx.png

Homework Statement



With which probability, starting in g, node d gets hit before node e?


Homework Equations





The Attempt at a Solution



I think the probability of hitting each node starting in g is the following:

p(g) = 1
p(c) = 1/2
p(a) = 1/3
p(d) = 1
p(b) = 1/3
p(f) = 1
p(e) = 0

Do I just have to add the probabilities from g to d and that's it?

Are the arcs directed or undirected? For example, from 'a' can we go just to 'b' and 'd', or can we also go back to 'c'? That will make a big difference to the probabilities.

RGV
 
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  • #8
Joffan said:
On a random walk that terminates on reaching either d or e:

- from g, what is the probability of reaching a?
- from c, what is the probability of reaching a?
- from f, what is the probability of reaching b?


I guess 1 in all cases.


Ray Vickson said:
Are the arcs directed or undirected? For example, from 'a' can we go just to 'b' and 'd', or can we also go back to 'c'? That will make a big difference to the probabilities.

RGV

I guess undirected (this is not specifically mentioned in the task but the image clearly shows an undirected graph since the arrows are missing)

thx for your replies
 
  • #9
is this right?

probability of hitting d (starting in g): 1+1+1/3
probability of hitting e (starting in g): 1+1+1/3+1/2
 
  • #10
scriby said:
is this right?

probability of hitting d (starting in g): 1+1+1/3
probability of hitting e (starting in g): 1+1+1/3+1/2

You need to keep your probabilities on a tighter rein... the total allocation of possible events should still only be 1

Once we reach a, what is the chance of reaching d before b?
 
  • #11
Joffan said:
You need to keep your probabilities on a tighter rein... the total allocation of possible events should still only be 1

Once we reach a, what is the chance of reaching d before b?

Modify the system by making both states d and e absorbing. Then, the probability of reaching d before e in the original system is the same as the probability of reaching d (at all) in the new system. Now apply standard equations for first-passage probabilities. In this way, if p(x) denotes the probability of reaching d (before e) starting from x, we have p(a) = 2/3, p(b) = 1/3, p(c) = 2/3, p(f) = 1/3 and p(g) = 2/3.

RGV
 
  • #12
Joffan said:
You need to keep your probabilities on a tighter rein... the total allocation of possible events should still only be 1

Once we reach a, what is the chance of reaching d before b?

1/3 ?

Ray Vickson said:
Modify the system by making both states d and e absorbing. Then, the probability of reaching d before e in the original system is the same as the probability of reaching d (at all) in the new system. Now apply standard equations for first-passage probabilities. In this way, if p(x) denotes the probability of reaching d (before e) starting from x, we have p(a) = 2/3, p(b) = 1/3, p(c) = 2/3, p(f) = 1/3 and p(g) = 2/3.

RGV

I can't follow your idea here. Making the states d and e absorbing means it is impossible to return once reaching those states right? This would mean their probabailities are always = 1 ?
Why is p(a)=2/3 , shouldn't it be only 1/3 ?
and why is p(c) = 2/3 , we only got 2 options to move away from c ?
 
  • #13
scriby said:
1/3 ?



I can't follow your idea here. Making the states d and e absorbing means it is impossible to return once reaching those states right? This would mean their probabailities are always = 1 ?
Why is p(a)=2/3 , shouldn't it be only 1/3 ?
and why is p(c) = 2/3 , we only got 2 options to move away from c ?

Yes, exactly: making them absorbing means you cannot return once reaching them. That is exactly why the probability of reaching d before e in the original system is the same as reaching d in the new system. Of course the probabilities of reaching d are not 1; d might never be reached. This is just like a game with two outcomes "win" or "lose", which ends when either of these outcomes is reached. However, you do not win with probability 1!

RGV
 
  • #14
scriby said:
Once we reach a, what is the chance of reaching d before b?
1/3 ?

No. From a, there is clearly a 1/3 chance to go to b, c or d on the next step, but if we go to c the walk has not finished. This 1/3 branch will eventually (inevitably) return to a, generating more probabilty for going to either b or d.
 
  • #15
I set up a little illustration in Excel that propagates probability through the network (but d and e are set as "sticky" - they retain all probability and send none to other nodes). Initial values (row 3) are g=1 and all others are zero.

(A4) =C3/2+B3/3
(B4) =A3/3+F3
(C4) =G3+A3/3
(D4) =A3/3+D3
(E4) =B3/3+E3
(F4) =B3/3
(G4) =C3/2

- then propagate these formulas down to extra rows.

It doesn't give the reasoning, but it illustrates the ideas and solution quite nicely.
 
  • #16
Joffan said:
I set up a little illustration in Excel that propagates probability through the network (but d and e are set as "sticky" - they retain all probability and send none to other nodes). Initial values (row 3) are g=1 and all others are zero.

(A4) =C3/2+B3/3
(B4) =A3/3+F3
(C4) =G3+A3/3
(D4) =A3/3+D3
(E4) =B3/3+E3
(F4) =B3/3
(G4) =C3/2

- then propagate these formulas down to extra rows.

It doesn't give the reasoning, but it illustrates the ideas and solution quite nicely.

There is no need to do this, although doing this might lead to some extra insights and help the OP better understand the problem. Instead, you can just write down the coupled linear equations for p(a), p(b), etc., and solve them. This is easy enough to do by hand, but if you insist on using EXCEL you can use the Solver tool to get the solution of the equations.

RGV
 
  • #17
Ray Vickson said:
There is no need to do this, although doing this might lead to some extra insights and help the OP better understand the problem. Instead, you can just write down the coupled linear equations for p(a), p(b), etc., and solve them. This is easy enough to do by hand, but if you insist on using EXCEL you can use the Solver tool to get the solution of the equations.

RGV

Of course there's no need to do this, except for the insights and understanding. That's the whole point.
 
  • #18
Ray Vickson said:
There is no need to do this, although doing this might lead to some extra insights and help the OP better understand the problem. Instead, you can just write down the coupled linear equations for p(a), p(b), etc., and solve them. This is easy enough to do by hand, but if you insist on using EXCEL you can use the Solver tool to get the solution of the equations.

RGV

Could you please tell me how to do that? Because I think that's the point I don't really understand (how to add the probabilities)
 
  • #19
I think, scriby, that you need to understand how to apportion the probabilities - adding is simple.

Starting with the initial known state which is prob=1, subsequent steps will typically subdivide that probability across different nodes. If you have reached node a with probability of (say) 0.6 at a certain point in the walk, then the allocation of probability from that node is 1/3 of 0.6 to each of the branch nodes - 0.2 each to b, c and d - for the next step.

There are simplifications that can be made in this case, because there is no need to consider the system in a strict step-by-step fashion to answer the question. But the basic understanding of how the probability divides out amongst the nodes is important too.
 

Related to What is the Probability of Reaching Node D Before Node E Starting from Node G?

1. What is a random walk in a graph?

A random walk in a graph is a mathematical concept that describes a process of moving through a graph from one node to another in a random manner. In other words, at each step, the next node is chosen randomly based on the available connections from the current node.

2. How is a random walk different from a regular graph traversal?

A random walk differs from a regular graph traversal in that it does not follow a predetermined path or algorithm. Instead, it follows a stochastic process where each step is chosen randomly, without any specific criteria or rules.

3. What is the purpose of studying random walks in graphs?

Studying random walks in graphs has various applications in fields such as physics, computer science, and social sciences. It can help in understanding the structure and properties of networks, predicting the spread of diseases, and designing efficient algorithms for graph-based problems.

4. Can a random walk get stuck in a graph?

Yes, a random walk can get stuck in a graph if there are no available connections from the current node. This is known as a trapping state, and it can occur in certain types of graphs, such as disconnected graphs or graphs with isolated nodes.

5. How can random walks be used for data analysis?

Random walks can be used for data analysis to identify patterns and relationships in a graph. By simulating multiple random walks, we can gather statistical information about the graph's structure, such as the average path length, the clustering coefficient, and the centrality of nodes. This information can be useful in various data analysis tasks, such as anomaly detection and community detection.

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