Body: <p>I'm having trouble beating an AI in Isolation game: <a href="https://en.wikipedia.org/wiki/Isolation_(board_game)" rel="nofollow noreferrer">https://en.wikipedia.org/wiki/Isolation_(board_game)</a> with 3 queens on a 7x7 board. I tried applying alpha beta iteration with a scoring function on the state. I tried 3 scoring functions:</p>
  <ol>
  <li>(0.75/# moves taken) * number of legal moves - (# moves taken/0.75) * number of opponent legal moves</li>
  <li>number of legal moves - 3 * number of opponent legal moves</li>
  <li>3 * number of legal moves - number of opponent legal moves</li>
  </ol>
  <p>The first is an annealed aggressive strategy so the agent gets more aggressive as the game goes longer. The 2nd is a pure aggression strat and the last is a pure defensive strat. None of them consistently beat standard alpha beta iteration with the state scoring function: number of legal moves -  number of opponent legal moves. They all broke roughly even.</p>
  <p>Any suggestions of scoring state functions or search algorithms are appreciated. The search has a limit of 6000 seconds per turn though.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-02-08T10:53:12.527Z
Comments.Text: What is your main **specific** question here? Please, choose one specific question and put it in the body **and** title of your post to clarify what you're asking here.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-02-08T16:56:11.250Z
Comments.Text: I'm simply asking for a search algorithm with a cost function that can do better than iterative alpha beta
Comments.UserDisplayName: user8714896
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-02-09T17:31:27.040Z
Comments.Text: Is your question somehow related to this: https://ai.stackexchange.com/q/5174/2444?
Comments.UserDisplayName: nbro
Tags: <alpha-beta-pruning><iddfs>
Title: Beating iterative alpha beta search in Isolation Game
UserDisplayName: user8714896
ThreadText: # Beating iterative alpha beta search in Isolation Game
  
  (Asked by: username_0 on 2021-02-07)
  
  I'm having trouble beating an AI in Isolation game: <https://en.wikipedia.org/wiki/Isolation_(board_game)> with 3 queens on a 7x7 board. I tried applying alpha beta iteration with a scoring function on the state. I tried 3 scoring functions:
  
  1. (0.75/# moves taken) \* number of legal moves - (# moves taken/0.75) \* number of opponent legal moves
  2. number of legal moves - 3 \* number of opponent legal moves
  3. 3 \* number of legal moves - number of opponent legal moves
  
  The first is an annealed aggressive strategy so the agent gets more aggressive as the game goes longer. The 2nd is a pure aggression strat and the last is a pure defensive strat. None of them consistently beat standard alpha beta iteration with the state scoring function: number of legal moves - number of opponent legal moves. They all broke roughly even.
  
  Any suggestions of scoring state functions or search algorithms are appreciated. The search has a limit of 6000 seconds per turn though.
  
  **Tags:** alpha-beta-pruning, iddfs
  > **Comments:**
  > **username_1**: What is your main **specific** question here? Please, choose one specific question and put it in the body **and** title of your post to clarify what you're asking here.  
  > **username_0**: I'm simply asking for a search algorithm with a cost function that can do better than iterative alpha beta  
  > **username_1**: Is your question somehow related to this: https://ai.stackexchange.com/q/5174/2444?  
  
  ---
  
  ## 0 answers
  
  