hdrqn
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Updated
Nov 15, 2018 - Python
hdrqn
A POMDP solver using Littman-Cassandra's Witness algorithm.
Thompson Sampling based Monte Carlo Tree Search for MDPs and POMDPs
Compressed belief-state MDPs in Julia compatible with POMDPs.jl
A collection of pomdp domains in robotics.
The goal of the project is to make a robot plan its path from a source to the destination and reach the destination only by evidence and its previous transition.
Interface for defining discrete and continuous-space MDPs and POMDPs in python. Compatible with the POMDPs.jl ecosystem.
Pytorch code for "Learning Belief Representations for Imitation Learning in POMDPs" (UAI 2019)
Adaptive stress testing of black-box systems within POMDPs.jl
Concise and friendly interfaces for defining MDP and POMDP models for use with POMDPs.jl solvers
Julia Implementation of the POMCP algorithm for solving POMDPs
A gallery of POMDPs.jl problems
Implementation of the Deep Q-learning algorithm to solve MDPs
Online solver based on Monte Carlo tree search for POMDPs with continuous state, action, and observation spaces.
The PO-UCT algorithm (aka POMCP) implemented in Julia
A framework to build and solve POMDP problems. Documentation: https://h2r.github.io/pomdp-py/
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