This repo contains all the stuff I encountered while playing OverTheWire games.
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Updated
Dec 25, 2020
This repo contains all the stuff I encountered while playing OverTheWire games.
Repository for the course project done as part of CS-747 (Foundations of Intelligent & Learning Agents) course at IIT Bombay in Autumn 2022.
Simple Implementations of Bandit Algorithms in python
Deep Reinforcement Learning Agents in Pytorch in a modular framework
Foundations of Intelligent and Learning Agenet
A two armed bandit simulation and comparison with theoritical convergence
Coursework, Stochastic Models and Optimization, BSE, Term 3, Class of 2022
Implementation of the prophet inequalities
An exploration of multi-armed Bernoulli bandits in reinforcement learning, complete with experiments and observations.
TJHSST Artificial Intelligence Labs from the 2022-23 School Year with Dr. Gabor
lightweight contextual bandit library for ts/js
Code for our AJCAI 2020 paper: "Online Semi-Supervised Learning in Contextual Bandits with Episodic Reward".
This project provides a simulation of multi-armed bandit problems. This implementation is based on the below paper. https://arxiv.org/abs/2308.14350.
Implementation of the experiments for "Cooperative Online Learning with Feedback Graphs" Cesa-Bianchi, Cesari, Della Vecchia (https://arxiv.org/abs/2106.04982)
Implementation of Multi-Armed Bandit (MAB) algorithms UCB and Epsilon-Greedy. MAB is a class of problems in reinforcement learning where an agent learns to choose actions from a set of arms, each associated with an unknown reward distribution. UCB and Epsilon-Greedy are popular algorithms for solving MAB problems.
Code for our PRICAI 2022 paper: "Online Learning in Iterated Prisoner's Dilemma to Mimic Human Behavior".
Python implementation of common RL algorithms using OpenAI gym environments
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