Skip to content

Model Training & Adaptation

Exploration-exploitation tradeoff

Balancing trying new options with choosing options that have worked well before.

Example

A recommendation system sometimes tests a new option instead of repeating a successful one.

Why people use it

It helps balance learning about new choices with using choices already known to work.

What you'll hear

“Should we try something new or use the reliable option?”

What this means for you

Set limits on experimentation when actions affect people or resources.

Can you control it?

No

No direct control. This describes a wider issue, concept or result rather than something you can simply switch on or off in a tool.

Common questions

Can the best option change over time?
Yes. Changing conditions can make a previously successful choice less useful, giving fresh exploration a purpose.
Can always choosing the current favorite miss something better?
Yes. An untried option may be better but never get a chance to show it.
Can experimentation have a real cost?
Yes. A less successful choice can affect customers, time or money while the system is learning.

Related terms

Still have questions?

Up to 500 characters.

Ask LATHIC about AI. Relevant glossary entries may be included.

Your question, the glossary entries it matches, and a rotating pseudonymous identifier go to Microsoft Azure’s OpenAI service through Vercel AI Gateway to generate an answer. Zero retention and no training are required of the provider, and LATHIC does not save your question or answer. Privacy Notice