counterfactual-regret-minimization | Counterfactual regret minimization algorithm for Kuhn poker
kandi X-RAY | counterfactual-regret-minimization Summary
kandi X-RAY | counterfactual-regret-minimization Summary
counterfactual-regret-minimization is a Python library. counterfactual-regret-minimization has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.
This is supplementary code for Counterfactual regret minimization blog post here.
This is supplementary code for Counterfactual regret minimization blog post here.
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Quality
Security
License
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Support
counterfactual-regret-minimization has a low active ecosystem.
It has 117 star(s) with 38 fork(s). There are 10 watchers for this library.
It had no major release in the last 6 months.
counterfactual-regret-minimization has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of counterfactual-regret-minimization is current.
Quality
counterfactual-regret-minimization has 0 bugs and 0 code smells.
Security
counterfactual-regret-minimization has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
counterfactual-regret-minimization code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
counterfactual-regret-minimization is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
Reuse
counterfactual-regret-minimization releases are not available. You will need to build from source code and install.
Build file is available. You can build the component from source.
Installation instructions are not available. Examples and code snippets are available.
counterfactual-regret-minimization saves you 113 person hours of effort in developing the same functionality from scratch.
It has 287 lines of code, 43 functions and 8 files.
It has medium code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed counterfactual-regret-minimization and discovered the below as its top functions. This is intended to give you an instant insight into counterfactual-regret-minimization implemented functionality, and help decide if they suit your requirements.
- Performs the cfr search
- True if the position is a chance
- Return a random node
- Returns the probability of the action
- True if the action is a terminal
- Evaluate the utilities for a given state
- Get the play for the given action
- Calculate the cumulative sigma for the given action
- Calculate cumulative recall for a given action
- Calculate the sigma of the cumulative distribution
- Recursively update sigma
- Returns the evaluation of the node
- Return the value of the game
- Computes the value of the given node
- Compute the nash_equilibrium
- Compute the Neumann reciprocal relationship
- Run Cfrility
Get all kandi verified functions for this library.
counterfactual-regret-minimization Key Features
No Key Features are available at this moment for counterfactual-regret-minimization.
counterfactual-regret-minimization Examples and Code Snippets
No Code Snippets are available at this moment for counterfactual-regret-minimization.
Community Discussions
No Community Discussions are available at this moment for counterfactual-regret-minimization.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install counterfactual-regret-minimization
You can download it from GitHub.
You can use counterfactual-regret-minimization like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use counterfactual-regret-minimization like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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