A lightweight C++ behavior tree library with a QT5 remote debugger and optional Lua bindings for AI logic.
SimpleAI is a lightweight C++ library for implementing AI behavior trees, commonly used in game development and simulations. It provides a hierarchical node-based system to model complex AI decision logic, along with a QT5-based remote debugger for real-time visualization and optional Lua bindings for scripting.
Game developers and simulation engineers who need a straightforward, embeddable behavior tree solution for C++ projects, particularly those requiring debugging tools and scripting flexibility.
Developers choose SimpleAI for its minimal dependencies, cross-platform compatibility, and integrated remote debugging capabilities, offering a practical alternative to heavier AI frameworks without sacrificing essential features.
SimpleAI is a small C++ AI behaviour tree based library with a QT5 based remote debugger (and with optional LUA bindings) released under MIT.
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Uses only Lua 5.3 and tinyxml2, both optional and can be disabled, keeping the library lightweight and easy to integrate into projects without bloat.
Supports major compilers like clang, gcc, and MSVC, with build system options including CMake, automake, and qmake for flexible development across platforms.
Includes a QT5-based graphical tool for real-time visualization and debugging of behavior trees, a rare feature in minimal libraries that enhances development efficiency.
Lua bindings allow for dynamic behavior tree definition and modification, adding scripting flexibility without mandatory overhead, as noted in the README.
Focuses on simplicity and performance, avoiding unnecessary complexity for efficient AI decision-making in games and simulations, as highlighted in the philosophy.
The remote debugger requires QT5, which can be a heavy addition for projects not already using QT, increasing setup complexity and potential licensing concerns.
Documentation is primarily Doxygen-generated, lacking beginner tutorials or comprehensive guides, making it less accessible for those new to behavior trees or C++.
The README notes that precompiled headers should be set up to reduce compile times, indicating potential performance issues in development workflows.
Exclusively focuses on behavior trees without built-in support for other AI paradigms, such as state machines, which might require integrating additional libraries for broader needs.