Body: <p>My agent receives <span class="math-container">$1, 0, -1$</span> rewards for winning, drawing, and losing the game, respectively. What would be the consequences of setting reward to <span class="math-container">$-1$</span> for draws? Would that encourage the agent to win more or will it have no effect at all? Is it appropriate to do so?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-11-16T08:46:04.007Z
Comments.Text: It can depend on many factors, for instance, your environment and data specifics. So, perhaps, there are no generic answers. Only some specifics observed during my experiments - it can slow down learning and create suboptimal agents which tend to make too risky decisions. Why don't you try it with your case and compare with my observations? That would be an answer for your question.
Comments.UserDisplayName: Stepan Novikov
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-11-16T12:47:21.570Z
Comments.Text: Yes, maybe you should tell us what zero-sum game you are trying to solve with RL, so that people could also try out your setting.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-11-16T23:21:56.063Z
Comments.Text: Thanks for answers. This time I'm trying to solve the mancala game for different board sizes. My project is still on early stage (bugs/subtle bugs), so it's hard for me to really isolate the affect in this case. I will share the results if/when I make progress, but I can see now how it makes sense that this would experiment-specific.
Comments.UserDisplayName: mark mark
Tags: <reinforcement-learning><reward-design><reward-functions><zero-sum-games>
Title: How can I discourage the RL agent from drawing in a zero-sum game?
UserDisplayName: mark mark
ThreadText: # How can I discourage the RL agent from drawing in a zero-sum game?
  
  (Asked by: username_0 on 2020-11-15)
  
  My agent receives $1, 0, -1$ rewards for winning, drawing, and losing the game, respectively. What would be the consequences of setting reward to $-1$ for draws? Would that encourage the agent to win more or will it have no effect at all? Is it appropriate to do so?
  
  **Tags:** reinforcement-learning, reward-design, reward-functions, zero-sum-games
  > **Comments:**
  > **username_1**: It can depend on many factors, for instance, your environment and data specifics. So, perhaps, there are no generic answers. Only some specifics observed during my experiments - it can slow down learning and create suboptimal agents which tend to make too risky decisions. Why don't you try it with your case and compare with my observations? That would be an answer for your question.  
  > **username_2**: Yes, maybe you should tell us what zero-sum game you are trying to solve with RL, so that people could also try out your setting.  
  > **username_0**: Thanks for answers. This time I'm trying to solve the mancala game for different board sizes. My project is still on early stage (bugs/subtle bugs), so it's hard for me to really isolate the affect in this case. I will share the results if/when I make progress, but I can see now how it makes sense that this would experiment-specific.  
  
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  ## 0 answers
  
  