Can an evolutionary algorithm adapt to a changing environment? From this SE question:


  Will be AI able to adapt, to different environments and changes.


This is my attempt at interpreting that question.

Evolutionary algorithms are useful for solving optimization problems...by measuring the "fitness" of various probable solutions and then  of an algorithm through the process of natural selection.

Suppose, the "fitness calculation"/"environment" is changed in mid-training (as could easily happen in real-life scenarios where people may desire different solutions at different times). Would evolutionary algorithms be able to respond effectively to this change?
The core question to whether or not an AI is adaptable or not is whether or not it supports online learning. That doesn't mean using the Internet to learn things; that means continuing to accept training data during the functioning of the system.

This is (mostly) independent of the underlying architecture; in evolutionary approaches one can continue to breed generations with a shifting fitness function or with neural networks one can continue to backpropagate errors, and so on with other approaches.