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

Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022

Python implementation of POMDP framework and PBVI & POMCP algorithms.

Online Replanning in Belief Space for Partially Observable Task and Motion Problems

Clean baseline implementation of PPO using an episodic TransformerXL memory

Gym-like extensions for POMDP

Adaptive Attention Span for Reinforcement Learning

Partially Observable Process Gym

This repository contains the code for RL for POMDPs through learning an Approximate Information State.

When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment, NeurIPS 2023 (oral)

Goal Oriented Dialog System

Scallable partially observable and/or non-Markovian gridworld for planning or reinforcement learning

Implementation of point-based value iteration (for POMDPs)

MIT Planning Algorithms Class Implementations

Task models for human robot collaboration

using recurrent networks(LSTM) to solve POMDPs

An implementation of the CORPP algorithm, described in a paper by Shiqi Zhang and Peter Stone

QMDP Net fork (python 3 compatible)

DQN in Dynamic Channel Access

AINE-DRL is a deep reinforcement learning (DRL) baseline framework. AINE means "Agent IN Environment".