Stars
Posthoc is a way to build simple and effective visualisations ✨ for sequential decision-making algorithms, such as search.
ProbFD is an extension of the Fast Downward planning system tailored for fully-observable probabilistic planning.
Code for solving LP on GPU using first-order methods
Model Context Protocol (MCP) server for constraint optimization and solving"
Constraint Programming and Modeling library in Python, based on numpy, with direct solver access.
A lighweight Python coding agent that writes, executes, and iterates on code through natural language instructions. Easily adaptable with custom project prompts.
Optimization Modeling Using mip Solvers and large language models
Automatically exported from code.google.com/p/mdp-engine
The Gourmand Planner, by Andrey Kolobov, Peng Dai, Mausam, and Dan Weld
A curated list of online resources for probabilistic planning: papers, software and research groups around the world!
A Lazy Clause Generation solver with a focus on modularity and maintainability in addition to speed
A Lazy Clause Generation Constraint Programming solver written in Rust.
OpenSSA: Small Specialist Agents based on Domain-Aware Neurosymbolic Agent (DANA) architecture for industrial problem-solving
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
Rust Progmmable Interface for Domain-Independent Dynamic Programming (RPID)
Simple and easily configurable 3D FPS-game-like environments for reinforcement learning
Simple and easily configurable grid world environments for reinforcement learning
A simple framework for experimenting with Reinforcement Learning in Python.
Python package to read and write vehicle routing problem instances.
Pathfinding and search testbed/visualization suite. Current code is in PDB-refactor branch.