# bandit learning

Published articles for bandit learning.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## Bandits and Stocks

DevFeed: [Bandits and Stocks](<https://devfeed.tech/articles/bandits-and-stocks-40335.md>)

Original publisher: [Read original article](<https://www.jeremykun.com/2013/12/09/bandits-and-stocks/>)

Published: 2013-12-09T09:00:52Z

Content type: tutorial

Language: en

Sources: [Jeremy Kun](<https://devfeed.tech/sources/jeremy-kun.md>)

Topics: [Programming](<https://devfeed.tech/topics/programming.md>), [Machine Learning & Artificial Intelligence](<https://devfeed.tech/topics/machine-learning-artificial-intelligence.md>)

Tags: [algorithm](<https://devfeed.tech/tags/algorithm.md>), [algorithms](<https://devfeed.tech/tags/algorithms.md>), [bandit-learning](<https://devfeed.tech/tags/bandit-learning.md>), [bandits](<https://devfeed.tech/tags/bandits.md>), [exp3](<https://devfeed.tech/tags/exp3.md>), [experimental](<https://devfeed.tech/tags/experimental.md>), [finance](<https://devfeed.tech/tags/finance.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [programming](<https://devfeed.tech/tags/programming.md>), [python](<https://devfeed.tech/tags/python.md>), [stocks](<https://devfeed.tech/tags/stocks.md>), [trading](<https://devfeed.tech/tags/trading.md>), [ucb1](<https://devfeed.tech/tags/ucb1.md>)

### AI overview

This article experiments with the UCB1 and Exp3 bandit-learning algorithms on stock-trading data to compare their performance under stochastic and adversarial assumptions. It emphasizes that the model is simplistic and does not solve stock trading.

### Source excerpt

So far in this series we've seen two nontrivial algorithms for bandit learning in two different settings. The first was the UCB1 algorithm, which operated under the assumption that the rewards for the trials were independent and stochastic. That is, each slot machine was essentially a biased coin flip, and the algorithm was trying to find the machine with the best odds. The second was the Exp3 algorithm, which held the belief that the payoffs were arbitrary.

## Adversarial Bandits and the Exp3 Algorithm

DevFeed: [Adversarial Bandits and the Exp3 Algorithm](<https://devfeed.tech/articles/adversarial-bandits-and-the-exp3-algorithm-40333.md>)

Original publisher: [Read original article](<https://www.jeremykun.com/2013/11/08/adversarial-bandits-and-the-exp3-algorithm/>)

Published: 2013-11-08T09:00:40Z

Content type: tutorial

Language: en

Sources: [Jeremy Kun](<https://devfeed.tech/sources/jeremy-kun.md>)

Topics: [Machine Learning & Artificial Intelligence](<https://devfeed.tech/topics/machine-learning-artificial-intelligence.md>), [Algorithm](<https://devfeed.tech/topics/algorithm.md>), [Learning](<https://devfeed.tech/topics/learning.md>)

Tags: [algorithm](<https://devfeed.tech/tags/algorithm.md>), [bandit-learning](<https://devfeed.tech/tags/bandit-learning.md>), [bandits](<https://devfeed.tech/tags/bandits.md>), [exp3](<https://devfeed.tech/tags/exp3.md>), [exploitation](<https://devfeed.tech/tags/exploitation.md>), [exploration](<https://devfeed.tech/tags/exploration.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [mathematics](<https://devfeed.tech/tags/mathematics.md>), [multiplicative-weights-update-algorithm](<https://devfeed.tech/tags/multiplicative-weights-update-algorithm.md>), [programming](<https://devfeed.tech/tags/programming.md>), [python](<https://devfeed.tech/tags/python.md>)

### AI overview

This article introduces adversarial bandit learning and explains how the Exp3 algorithm addresses decisions with uncertain outcomes. It contrasts adversarial payoffs with the simpler stochastic setting and frames success relative to the best single action over repeated trials.

### Source excerpt

In the last twenty years there has been a lot of research in a subfield of machine learning called Bandit Learning. The name comes from the problem of being faced with a large sequence of slot machines (once called one-armed bandits) each with a potentially different payout scheme. The problems in this field all focus on one central question: If I have many available actions with uncertain outcomes, how should I act to maximize the quality of my results over many trials?

## Optimism in the Face of Uncertainty: the UCB1 Algorithm

DevFeed: [Optimism in the Face of Uncertainty: the UCB1 Algorithm](<https://devfeed.tech/articles/optimism-in-the-face-of-uncertainty-the-ucb1-algorithm-40332.md>)

Original publisher: [Read original article](<https://www.jeremykun.com/2013/10/28/optimism-in-the-face-of-uncertainty-the-ucb1-algorithm/>)

Published: 2013-10-28T11:42:55Z

Content type: tutorial

Language: en

Sources: [Jeremy Kun](<https://devfeed.tech/sources/jeremy-kun.md>)

Topics: [Algorithm](<https://devfeed.tech/topics/algorithm.md>), [Mathematics](<https://devfeed.tech/topics/mathematics.md>), [Data Science](<https://devfeed.tech/topics/data-science.md>)

Tags: [algorithm](<https://devfeed.tech/tags/algorithm.md>), [bandit-learning](<https://devfeed.tech/tags/bandit-learning.md>), [bandits](<https://devfeed.tech/tags/bandits.md>), [big-o-notation](<https://devfeed.tech/tags/big-o-notation.md>), [calculus](<https://devfeed.tech/tags/calculus.md>), [confidence-bounds](<https://devfeed.tech/tags/confidence-bounds.md>), [exploitation](<https://devfeed.tech/tags/exploitation.md>), [exploration](<https://devfeed.tech/tags/exploration.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [mathematics](<https://devfeed.tech/tags/mathematics.md>), [programming](<https://devfeed.tech/tags/programming.md>), [python](<https://devfeed.tech/tags/python.md>), [random-variables](<https://devfeed.tech/tags/random-variables.md>), [randomized-algorithm](<https://devfeed.tech/tags/randomized-algorithm.md>), [science](<https://devfeed.tech/tags/science.md>)

### AI overview

This tutorial introduces the multi-armed bandit problem as a model of the exploration-exploitation tradeoff and presents the UCB1 algorithm, which the article describes as performing close to optimally.

### Source excerpt

startups The software world is always atwitter with predictions on the next big piece of technology. And a lot of chatter focuses on what venture capitalists express interest in. As an investor, how do you pick a good company to invest in? Do you notice quirky names like "Kaggle" and "Meebo," require deep technical abilities, or value a charismatic sales pitch? When it comes to innovation in software engineering and computer science, and that as a society we should value big pushes forward much more than we do.