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https://github.com/beegass/ai-project2

In the class CS-4341, Artificial Intelligence, we were tasked to build an agent that could play the game of Gomoku. In order to achieve this the team implemented the MiniMax algorithm, Alpha-beta-pruning as well as our own understanding of evualtion function to facilitate the previous two algorithms. Additionally to aide in the agents compentency the team built, from scratch, a linear neural network.

https://github.com/beegass/ai-project2

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Committers with academic emails
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    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (3.2%) to scientific vocabulary

Keywords

alpha-beta-pruning artificial-intelligence evaluation-functions gomoku minimax-algorithm
Last synced: 5 months ago · JSON representation

Repository

In the class CS-4341, Artificial Intelligence, we were tasked to build an agent that could play the game of Gomoku. In order to achieve this the team implemented the MiniMax algorithm, Alpha-beta-pruning as well as our own understanding of evualtion function to facilitate the previous two algorithms. Additionally to aide in the agents compentency the team built, from scratch, a linear neural network.

Basic Info
Statistics
  • Stars: 1
  • Watchers: 2
  • Forks: 0
  • Open Issues: 6
  • Releases: 0
Topics
alpha-beta-pruning artificial-intelligence evaluation-functions gomoku minimax-algorithm
Created over 5 years ago · Last pushed almost 5 years ago
Metadata Files
Readme Changelog

README.md

AI_Project2

In the class CS-4341, Artificial Intelligence, we were tasked to build an agent that could play the game of Gomoku. In order to achieve this the team implemented the MiniMax algorithm, Alpha-beta-pruning as well as our own understanding of evualtion function to facilitate the previous two algorithms. Additionally to aide in the agents compentency the team built, from scratch, a linear neural network.

Instructions to run the program: COMING SOON

Owner

  • Name: Bryan
  • Login: BeeGass
  • Kind: user
  • Location: Cambridge, MA
  • Company: @USArmyResearchLab

Research Engineer interested in SSMs

GitHub Events

Total
Last Year

Committers

Last synced: over 1 year ago

All Time
  • Total Commits: 120
  • Total Committers: 3
  • Avg Commits per committer: 40.0
  • Development Distribution Score (DDS): 0.575
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Bryan 4****y 51
Collin Broderick s****n@g****m 46
Erik e****0@g****m 23

Issues and Pull Requests

Last synced: over 1 year ago

All Time
  • Total issues: 6
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 2
  • Total pull request authors: 0
  • Average comments per issue: 0.67
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
Issue Authors
  • cabroderick (3)
  • BeeGass (3)
Pull Request Authors
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