MDPs and POMDPs in Julia - An interface for defining, solving, and simulating fully and partially observable Markov decision processes on discrete and continuous spaces.

An extension of POMDPs.jl for Mixed Observability MDPs

Compressed belief-state MDPs in Julia for reinforcement learning and sequential decision making. Part of the POMDPs.jl community.

Online solver based on Monte Carlo tree search for POMDPs with continuous state, action, and observation spaces.

Simple particle filter implementation in Julia - works with POMDPs.jl models or others.

The PO-UCT algorithm (aka POMCP) implemented in Julia

A Julia implementation of the Gap Heuristic Search online planning algorithm, for use with the POMDPs.jl ecosystem.

Monte Carlo Tree Search for Markov decision processes using the POMDPs.jl framework