Markov Decision Processes Python Packages

csle-collector

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

csle-ryu

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

csle-common

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

csle-attacker

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

gym-csle-stopping-game

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

csle-defender

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

csle-agents

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

csle-system-identification

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

csle-cli

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

csle-rest-api

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

csle-base

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

csle-cluster

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

gym-csle-intrusion-response-game

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

csle-tolerance

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

gym-csle-apt-game

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

gym-csle-cyborg

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

csle-attack-profiler

A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.

pomdp-py

A framework to build and solve POMDP problems. Documentation: https://h2r.github.io/pomdp-py/

ns-gym

A framework for modeling non-stationary Markov decision processes and the key decision making problems in these environments

quickpomdps

Describing and Solving POMDPs in Python

upgrade-policy-optimizer

A Python library for solving finite Markov Decision Processes using value iteration

mdpproblog

A probabilistic logic programming framework to represent and solve MDPs.

gridgym

An OpenAI Gym environment for resource and job management systems.