TLDR: Generic Algorithms, Decision Trees, Value Iteration, POMDPs, Bias-Variance. Data preprocessing using statistical techniques and visualization is crucial to understand and analyze the data before utilizing them to train a machine learning model. Several fundamental techniques for preprocessing are presented here.

A box-picking POMDP created using POMDPs.jl

POMDP for a programs funder and evaluator

This repo contains the work done on building the infrared component of our autonomous target detection framework named FALCO at the COHRINT LAB.

Proposing better macro actions set using recurrent neural networks conditioned on encoded environmental contexts

Trained Probabilistic Models for the NAO Robot in a Labyrinth

POMDP planning of collaborative robot tasks in assembly

🌫️ Fog of war chess for ios ⚔️

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policy generation using SARSOP, in Machine Learning, MDL | Spring 2021

Effective policy for running a set of elevators formulated using a POMDP

POMDP formulation and solution of the COVID-19 epidemic

Partially Observable Monte Carlo Planning algorithm (POMCP)

Planificación en Entornos con Incertidumbre

This project implements several methods for cost sensitive classification, based on a POMDP formalization, and an MDP formalization of the problem

Deep Q Learning for resolving Partially Observable MDP based on Minecraft environment

Code for NeurIPS paper: https://openreview.net/forum?id=5wdvW_hI7bP

This repo contains the work done on building the rgb component of our autonomous target detection framework named FALCO at the COHRINT LAB.

CS 238 Final Project: Deep Reinforcement Learning Agents that Run with Scissors