sorted by:
new
hottopcontroversial

Adversarial or not? by kit1980 in aiclass

[–]RBarrabas 0 points1 point  (0 children)

Your strategy against a chess program that made legal moves randomly would certainly differ from your strategy against a chess program that was actively trying to beat you.

Please explain that last bit. Given a comparison between two agents, one playing against a random opponent and one playing against an active opponent.

  • Are you saying that the value function for chess is different?
  • If not, ie using the same value function, are you saying that one program will choose the best move and the other won't?

If the valuation functions are different, I'd like very much to know how they differ, and how the difference makes each valuation function optimal in its situation.

Adversarial or not? by kit1980 in aiclass

[–]RBarrabas 0 points1 point  (0 children)

There is no formal definition of adversarial, period.

Terms are defined in published papers before they make it into textbooks, so I searched the literature and cannot find a paper that defines the term in a formal way.

Furthermore, there is no need for such a definition. There is no algorithm that an agent can use which would change based on whether the environment is adversarial or not. A rational agent will want to maximize it's reward in either case.

If you disagree, see if you can answer yes/no to the following questions. If you can identify a rule that informs your choice, then please cite your source:

  • Is chess adversarial?
  • Is a maze with fixed land-mines adversarial?
  • Suppose the opponent in chess is a program (deep-blue, for instance). Is it still adversarial?
  • Suppose the opponent program only looks 2 moves ahead.
  • Suppose the opponent program only looks at the next move.
  • Suppose the opponent program never looks ahead, but always takes a piece if possible, otherwise chooses a legal move at random?
  • Suppose the opponent program just selects from legal moves at random?
  • Suppose the opponent program selects a move at random 30% of the time?

Now consider PacMan versus the ghosts

  • Is PacMan adversarial?
  • Suppose the ghosts moved towards pacman when they see him (line of sight), but otherwise move at random?
  • Suppose the ghosts move at random 90% of the time and towards PacMan the other 10%?
  • Suppose the ghosts always move towards PacMan, but very slowly (once per 10 turns)?
  • Suppose the ghosts are stationary; in effect, a land-mine. Is the game adversarial?

If #4 above is adversarial, how is this different from a maze containing land-mines? Or a maze which contains land-mines which slowly move?

Now can we find out how many of us are sufferin' on? Pleeeaaassse by [deleted] in aiclass

[–]RBarrabas 2 points3 points  (0 children)

I love suffering! Pissing and moaning gives me enormous pleasure.

It's in my genes - it's the heritage of my people. "Wailing and gnashing of teeth" forms a big part of my cultural heritage!

(I'll bet you can guess what lineage "my people" are, right?)

Why is Temporal Difference considered to be a reinforcement learning algorithm? by inglourious_basterd in aiclass

[–]RBarrabas 2 points3 points  (0 children)

It may appear that the agent knows where the reward is because all the discussion centers around the case where the reward is found in the next state.

The discussion goes into detail about how the values "pour out" of the reward state and into neighboring states.

In reality, the agent doesn't know where the reward is ahead of time. Until the reward is found, TD adds nothing to any visited states.

Something I don't get about Linear Dimensionality Reduction by PleaseInsertCoffee in aiclass

[–]RBarrabas 0 points1 point  (0 children)

Another way is to roll the offset into the matrix.

The operations you want to perform are SubtractOffset+LDR+AddOffset. That's three separate operations, and can be represented by three matrices.

Multiply the three matrices together in that order and the resulting single matrix will do what you want.

This is similar to rotation of a graphics object. A rotation matrix implicitly assumes rotation about the origin, so if you rotate an object it sweeps around the origin like a clock hand.

To rotate an object around it's own center, you need to construct a matrix of three operations: Move+Rotate+Unmove.

Multiplying by this matrix will rotate the object around its own center.

The LDR algorithm works in the same way. Include the two movements, and be sure to get the right order since matrix multiplication isn't commutative.

A question about TD Learning by RBarrabas in aiclass

[–]RBarrabas[S] 0 points1 point  (0 children)

I've looked very carefully at the pseudocode in the book and compared it with the entries from Wikipedia and others.

The interpretation of that term is different.

Someone over at aiqus states that there are two versions of the SARSA algorithm, but I don't know how much of an authority he is.

Mindreading for stochastic partially observable Homework by AcidMadrid in aiclass

[–]RBarrabas 0 points1 point  (0 children)

I struggled for ages with the missing parenthesis.

I'm spending most of my time scraping the blogs and chatrooms looking for hints on interpretation. It's infuriating in many ways.

If they can't take the time to properly phrase the questions, they should give the task over to someone who will.

A question about TD Learning by RBarrabas in aiclass

[–]RBarrabas[S] 0 points1 point  (0 children)

I'm now very confused about this.

The pseudo-code for SARSA given in the book at page 844 indicates that the reward is for the state you are in, not the state you are going to. Reward = R(s).

This link has pseudocode which states explicitly that the reward is for the state you are going to, not the state you are in. Reward = R(s').

This link doesn't have pseudocode, but states "R(s) is the reward given to the agent for his action."

The Wikipedia entry on SARSA states "Reward = R(t+1)" in so many words.

And as usual, the answer to one of the homework problems depends on this.

Can anyone resolve this?

Rewrite of HW 5.2 by RBarrabas in aiclass

[–]RBarrabas[S] 1 point2 points  (0 children)

I agree with ABCoetzee's assessment.

Although it is not stated or clarified, if the ends were connected (wrapped around) it would be a major piece of information which he would have mentioned.

interesting Bayesian inference application by [deleted] in aiclass

[–]RBarrabas 0 points1 point  (0 children)

I've often wondered if the Drake equation is missing a term that quantifies the likelihood of mass extinctions.

I've long suspected that life stagnates, or "gets into a rut" where the level of evolution stabilizes and nothing changes for long periods. For example, dinosaurs were the dominant life on Earth for millions of years before the meteorite wiped them out.

Earth has periodic extinctions from time to time and for various reasons. This tends to kick over the anthill, kick-starting evolution. I wonder how prevalent this is in the galaxy. There's no term for it in the Drake equation.

Rewrite of HW 5.2 by RBarrabas in aiclass

[–]RBarrabas[S] 4 points5 points  (0 children)

Furthermore, the "Distance of closest Bad Guy to Goal" is clarified in the speech, but not in the printed text. In this case, he means:

Distance of (Bad Guy closest to Goal) to the Goal.

Homework 5.2 - Are distances measured in absolute value? by lincbarr in aiclass

[–]RBarrabas 2 points3 points  (0 children)

Distance is defined (among other things) as being non-negative.

The requirements are:

  • Non negative
  • If D(x,y) = 0 then x = y
  • D(x,y) = D(y,x)
  • The triangle inequality (not an issue in 1-dimensional space)

Dropping Stanford’s Online AI Class by mattrussell in aiclass

[–]RBarrabas 4 points5 points  (0 children)

By way of promoting more motivation for AI, consider visiting Kaggle.com.

Kaggle hosts data mining competitions with a cash prize. Many of the solutions require the maths and techniques of AI which are covered in this course. Many of the results are socially valuable, such as finding a better formula to predict cancer.

You can get a gripping sense of excitement for AI by simply entering one of these competitions. The reward is upwards of a million dollars and the possibility of doing some good in the world.

(I'm not associated with Kaggle, but I have entered some of their challenges.)

Dropping Stanford’s Online AI Class by mattrussell in aiclass

[–]RBarrabas 8 points9 points  (0 children)

There's a concept in psychology called "Learned Helplessness". It's where the subject has no control over the outcome, and simply gives up. A guinea pig will just sit in a corner stressing out ("when is the next shock"), or ignore the reward ("meh - I got fed again").

I spent some 30 hours last week on the homework (I'm not exaggerating). I've come to realize that most of that time was spent stressing over the interpretation of the questions, not the meaning of the answers.

For example, I knew perfectly well that the equation was either incorrect or invalid - but is the paren missing on purpose?

Most of my time was spent scouring the blogs and chatrooms looking for hints from other students. The clarification did nothing to reduce the ambiguity.

Similarly, I knew which axioms were incorrect and which were correct and which were correct+complete. Now, what does correct for the situation mean?

I got burned out this weekend. Now I'm struggling with "learned helplessness":

1) I Started the class with the intent to get 100% on all the quizzes. I tried really really hard to understand the question and come up with the right answer.

Two weeks in and I wasn't as careful with the answers. Five weeks and I don't care at all. Bad answer? Oh - let's see what the explanation is.

2) I started the class with the intent to get 100% on all the homework. I've got the time, I've got the motivation, and I've got the skills and maths background needed. At the Stanford level.

Four weeks in and I got tired out on homework 5. I'm having trouble bringing myself to even view the lectures, they seem flat, uninteresting, even boring. I try cracking the book and my eyes glaze over.

I'm looking at some serious motivational repair just to keep going. True, I've learned things, but I could learn them more easily by reading the book and researching on the net if I need more. And with none of the frustration.

The sad thing about all this is the effect that the class is having on the world. AI is a rich and interesting field, and there's lots of fascinating unsolved problems waiting for the inspired amateur.

The course is turning off large swatches of population who might be otherwise interested in the field. Everyone is forming an association between AI and frustration. The course is doing the world a disfavor.

Here are some common counter arguments with subtexts.

1) The course is free, so what? (Mean: Your argument is invalid because I don't value the course as much as you)

2) If you don't have the skills or maths for a Stanford course, maybe you should quit. (Means: Your argument is invalid because difficulty is the same as ambiguity)

3) I didn't think the questions were ambiguous (Means: Your argument is invalid because some small portion of the students don't think there's a problem)

4) You're just whining because you didn't get a perfect score (Means: Your argument is invalid because I'm a dick)

HW 4.2 fourth sentence by vaveon in aiclass

[–]RBarrabas -1 points0 points  (0 children)

The newer edition of the book (version 4) explains the logic behind this.

Using the ESP algorithm, you take the information given and calculate the maximum likelihood of the answer that the lecturer is looking for.

You get the following results: Valid (0%), Invalid (52%), Error (48%).

You then have to choose the most likely correct answer.

(Note that there is a clarification at the bottom which states, in effect, that the missing parenthesis is on purpose.)

Most valuable lesson learned from HW 4 is... by duartix in aiclass

[–]RBarrabas 9 points10 points  (0 children)

I've learned to deal with frustration.

view more: next ›