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Intelligent Agents: An A.I. View of Optimization

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Intelligent Agents: An A.I. View of Optimization

As a digital analyst or marketer, you know the importance of analytical decision making.

Go to any industry conference, blog, meet up, or Purchasing Directors Email Lists even just read the popular press, and you will hear and see topics like machine learning, artificial intelligence, and predictive analytics everywhere.

Because many of us don’t come from a technical/statistical background, this can be both a little confusing and intimidating.

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But don’t sweat it, in this post, I will try to clear up a some of this confusion by introducing a simple, yet powerful framework – the intelligent agent – which will help link these new ideas with familiar tools and concepts like A/B Testing and Optimization.

Note: the intelligent agent framework is used as the guiding principle in Russell and Norvig’s excellent text Artificial Intelligence: A Modern Approach – it’s an awesome book, and I recommend anyone who wants to learn more to go get a copy or check out their online AI course.

What is The Intelligent Agent?
You can think of an agent as an autonomous actor, or decision maker, that has a specific task to perform. Initially our agent may not be very good at its task. But over time, it tries to improve how well it performs, based on some specific objective or goal(s).

Example: Roomba

For example, consider the Roomba. Its task is to clean your floors, and it wants to finish its task in the least amount of time.


By making the connection between web optimization

and intelligent agents (specifically, software agents) we can tap into the methods and ideas from

AI and machine learning and apply them to our problem of marketing optimization.

The Basics of The Intelligent Agent
Let’s take a look at a basic components of the intelligent

agent and its environment, and walk through the major elements.

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