Answers.Body: <p>(using X for epsilon because keyboard)</p>
  
  <p>This is just a hypothesis, but if you have a maximising agent and a minimising agent, then the optimal outcome for A (maximising) is to sweep the board (X,0), while the optimal outcome for B (minimising) is (-X,0) because B is minimising A's score, not their own. </p>
  
  <p>A's optimal outcome is then complicated by the factor for sub-optimality, which we then imagine approaches zero.</p>
  
  <p>There seem to be a bunch of assumptions that are not articulated, though, if this hypothesis is true.</p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-01-23T08:58:02.663Z
Answers.LastActivityDate: 2017-01-23T08:58:02.663Z
Answers.UserDisplayName: Jnani Jenny Hale
Body: <p>I am drawing this question from Berkeley's AI course (also not sure if it is the correct place to ask, so I apologize ahead of time)
  <a href="https://inst.eecs.berkeley.edu/~cs188/pacman/course_schedule.html" rel="noreferrer">https://inst.eecs.berkeley.edu/~cs188/pacman/course_schedule.html</a></p>
  
  <p>Currently, I am working on section 3's Homework.</p>
  
  <p>My question is: the question (Part 1, question 6). Why is it that we can only guarantee that if the Min agent acts suboptimally, the best we can hope for is the following <a href="https://i.sstatic.net/lLe7K.png" rel="noreferrer"><img src="https://i.sstatic.net/lLe7K.png" alt="enter image description here"></a></p>
  
  <p>It seems that we can put any arbitrary value for the second node e.g. whey does it have to be -Episolon. It could be any range of values, e.g. Epsilon, in which case we would have optimised the Player A</p>
  
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2017-01-23T08:19:14.937Z
Comments.Text: Try to summarize your research question;please!
Comments.UserDisplayName: quintumnia
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2017-01-23T08:48:10.463Z
Comments.Text: The question is very simple - why does A's outcome on the second branch have to be minus epsilon? Couldn't it be any random number?
Comments.UserDisplayName: Jnani Jenny Hale
Tags: <research>
Title: Berkeley AI Course Question on Nearly Zero Sum Games
UserDisplayName: user2429446
ThreadText: # Berkeley AI Course Question on Nearly Zero Sum Games
  
  (Asked by: username_0 on 2017-01-22)
  
  I am drawing this question from Berkeley's AI course (also not sure if it is the correct place to ask, so I apologize ahead of time)
  <https://inst.eecs.berkeley.edu/~cs188/pacman/course_schedule.html>
  
  Currently, I am working on section 3's Homework.
  
  My question is: the question (Part 1, question 6). Why is it that we can only guarantee that if the Min agent acts suboptimally, the best we can hope for is the following [![enter image description here](https://i.sstatic.net/lLe7K.png)](https://i.sstatic.net/lLe7K.png)
  
  It seems that we can put any arbitrary value for the second node e.g. whey does it have to be -Episolon. It could be any range of values, e.g. Epsilon, in which case we would have optimised the Player A
  
  **Tags:** research
  > **Comments:**
  > **username_1**: Try to summarize your research question;please!  
  > **username_2**: The question is very simple - why does A's outcome on the second branch have to be minus epsilon? Couldn't it be any random number?  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2017-01-23. Score: 3
  
  (using X for epsilon because keyboard)
  
  This is just a hypothesis, but if you have a maximising agent and a minimising agent, then the optimal outcome for A (maximising) is to sweep the board (X,0), while the optimal outcome for B (minimising) is (-X,0) because B is minimising A's score, not their own.
  
  A's optimal outcome is then complicated by the factor for sub-optimality, which we then imagine approaches zero.
  
  There seem to be a bunch of assumptions that are not articulated, though, if this hypothesis is true.
  
  
  ---
  
  