GitHub / vismaychuriwala / Optimal-Strategies-in-Multi-Armed-Bandits
This repository contains several implementations of multi-armed bandit (MAB) agents applied to a simulated cricket match where an agent selects among different strategies with the goal of maximizing runs while minimizing the risk of getting out.
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PURL: pkg:github/vismaychuriwala/Optimal-Strategies-in-Multi-Armed-Bandits
Stars: 0
Forks: 0
Open issues: 0
License: None
Language: Python
Size: 17.6 KB
Dependencies parsed at: Pending
Created at: about 2 years ago
Updated at: 6 months ago
Pushed at: 6 months ago
Last synced at: 6 months ago
Topics: kl-divergence, multiarmed-bandits, proababilistic, regret-minimization, reinforcement-learning, risk-management, ucb-algorithm