Partially Observable Process Gym

Artificial Life and Intelligence. Researching behavior by nature and nurture simulation, deploying multi-agent reinforcement learning and evolving generational inheritance.

POMDP wrappers for OpenAI Gym

Certainty-Equivalent Expectation Maximization: a scalable algorithm for system identification of partially observed systems

A robot motion planning simulator that can efficiently navigate partially observable environments using deep learning

Multi-agent pursuit in matrix world (pursuitMW)

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

Grids, mountains, and mysterious problems. Solved with Partially-Observable Markov Decision Procesees. Created at Stanford University, by Pablo Rodriguez Bertorello

Recurrent Policies for Handling Partially Observable Environments

Heuristic Search Value Iteration for One-Sided Partially Observable Stochastic Games

Virtual reality (VR) environment for studying human-agent decision making.

cleaning agent where the environment is partially observable

Implementation of "A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes" (ICML)

Mastering MountainCar-v0: A Comprehensive Exploration of Reinforcement Learning Algorithms

Forward A* and Adaptive A* for navigation in partially known environments

An agent being trained to find its way in a stochastic and partially observable maze using SARSA and Q-Learning algorithms.