#计算机科学#Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers,...
MDPs and POMDPs in Julia - An interface for defining, solving, and simulating fully and partially observable Markov decision processes on discrete and continuous spaces.
A C++ framework for MDPs and POMDPs with Python bindings
A framework to build and solve POMDP problems. Documentation: https://h2r.github.io/pomdp-py/
#计算机科学#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.
Concise and friendly interfaces for defining MDP and POMDP models for use with POMDPs.jl solvers
Interface for defining discrete and continuous-space MDPs and POMDPs in python. Compatible with the POMDPs.jl ecosystem.
#计算机科学#Pytorch code for "Learning Belief Representations for Imitation Learning in POMDPs" (UAI 2019)
Adaptive stress testing of black-box systems within POMDPs.jl
Thompson Sampling based Monte Carlo Tree Search for MDPs and POMDPs
Julia Implementation of the POMCP algorithm for solving POMDPs
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.
Compressed belief-state MDPs in Julia for reinforcement learning and sequential decision making. Part of the POMDPs.jl community.
POMDP-based decision-making technique for Social Robots using ROS, Python and Julia