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50 search results found
Stanford Cs 221 Artificial Intelligence
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1,578
VIP cheatsheets for Stanford's CS 221 Artificial Intelligence
Pomdps.jl
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616
MDPs and POMDPs in Julia - An interface for defining, solving, and simulating fully and partially observable Markov decision processes on discrete and continuous spaces.
Ai Toolbox
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611
A C++ framework for MDPs and POMDPs with Python bindings
Hands On Reinforcement Learning With Python
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596
Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow
Curso Algebra Lineal
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353
Curso de Álgebra Lineal
Ecole
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259
Extensible Combinatorial Optimization Learning Environments
Sddp.jl
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257
Stochastic Dual Dynamic Programming in Julia
Pomdp Py
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149
A framework to build and solve POMDP problems. Documentation: https://h2r.github.io/pomdp-py/
Aalpy
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131
An Active Automata Learning Library Written in Python
Csle
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87
A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.
Wrighteaglebase
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83
WrightEagle Base Code for RoboCup Soccer Simulation 2D
Respy
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70
Framework for the simulation and estimation of some finite-horizon discrete choice dynamic programming models.
Markovjs
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66
Reinforcement Learning in JavaScript
Tsallis_actor_critic_mujoco
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58
Implementation of Tsallis Actor Critic method
Awesome Probabilistic Planning
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52
A curated list of online resources for probabilistic planning: papers, software and research groups around the world!
Mcts Agent Python
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48
Monte Carlo Tree Search (MCTS) is a method for finding optimal decisions in a given domain by taking random samples in the decision space and building a search tree accordingly. It has already had a profound impact on Artificial Intelligence (AI) approaches for domains that can be represented as trees of sequential decisions, particularly games and planning problems. In this project I used a board game called "HEX" as a platform to test different simulation strategies in MCTS field.
Learnsnake
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41
🐍 AI that learns to play Snake using Q-Learning (Reinforcement Learning)
Amazon Sagemaker Amazon Routing Challenge Sol
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39
AWS Last Mile Route Sequence Optimization
Emdp
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37
Easy MDPs and grid worlds with accessible transition dynamics to do exact calculations
Markov Decision Processes
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31
Implementation of value iteration algorithm for calculating an optimal MDP policy
Dvrp Stochastic Requests
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30
Online algorithms for solving large-scale dynamic vehicle routing problems with stochastic requests
Quickpomdps.jl
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28
Concise and friendly interfaces for defining MDP and POMDP models for use with POMDPs.jl solvers
Test Data Generation
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27
Test Data Generation
Relearn
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26
A Reinforcement Learning Library for C++11/14
Map Matching 2
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26
High Performance Map Matching with Markov Decision Processes (MDPs) and Hidden Markov Models (HMMs).
Hierarchical Decision Making For Autonomous Driving
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25
Rich literature review and discussion on the implementation of "Hierarchical Decision-Making for Autonomous Driving"
Practical_rl
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24
My solutions to Yandex Practical Reinforcement Learning course in PyTorch and Tensorflow
Qoco
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20
A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning for Mobile Edge Computing
Rl Short Course
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18
Reinforcement Learning Short Course
Ruspy
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15
Python package for the simulation and estimation of a prototypical infinite-horizon dynamic discrete choice model based on Rust (1987)
Cs7641 Assignment4
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14
CS7641 - Machine Learning - Assignment 4 - Markov Decision Processes
Mdpn
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13
Unified notation for Markov Decision Processes PO(MDP)s
Lifescripts
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13
Automating various decisions stochastically, starting with my current coin-based intermittent fasting and dice-based kettlebell.
Pomdp
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13
R package for Partially Observable Markov Decision Processes
Quickpomdps
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12
Interface for defining discrete and continuous-space MDPs and POMDPs in python. Compatible with the POMDPs.jl ecosystem.
Ws 18 19 Deep Learning Tutorial
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12
Deep Learning and Artificial Intelligence Tutorial @ LMU WS 2018/19
Npgi
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10
Non-linear policy graph improvement - planning for Dec-POMDPs
Jajapy
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9
Baum-Welch for all kind of Markov models
Pomcp.jl
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9
Julia Implementation of the POMCP algorithm for solving POMDPs
Artificial Intelligence
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8
Artificial Intelligence + Deep Learning
Mdp_path_planning
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8
This repository contains the MATLAB code to devise an optimal policy for the motion of the robot given the obstacles and world boundaries. This file contains implementation to a specific environment wiht known parameters and obstacles, but can easily be modified or generalized for any environment. The code was linked to the V-Rep simulation environment and tested.
Mdpbiome
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7
microbiome engineering through prescriptive perturbations
Randoms
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7
Tinkering and Playing around!
Reinforcementlearning
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6
Reinforcement Learning algorithms with nothing abstracted away
Artificial Intelligence The Pacman Projects
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6
Pacman Artificial Intelligence Python project for UC Berkeley CS188 Intro to AI
Markov Chain
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6
Library for computations with markov chains and probability matrices
Frozen Lake Openai Gym
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5
Implementation of RL Algorithms in Openai Gym Frozen-Lake Environment
Mcts Agent Cythonized
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5
MONTE Carlo Tree Search (MCTS) is a method for finding optimal decisions in a given domain by taking random samples in the decision space and building a search tree accordingly. It has already had a profound impact on Artificial Intelligence (AI) approaches for domains that can be represented as trees of sequential decisions, particularly games and planning problems. In this project I used a board game called "HEX" as a platform to test different simulation strategies in MCTS field.
Ee6204
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5
EE6204 Systems Analysis
Everything Financial Engineering
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5
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