@inproceedings {pub2585,
	title = {What Are Dynamic Optimization Problems?},
	author = {Haobo Fu AND Peter R. Lewis AND Bernhard Sendhoff AND Ke Tang AND Xin Yao},
	year = {2014},
	month = {July},
	abstract = {Dynamic Optimization Problems (DOPs) have
been widely studied using Evolutionary Algorithms (EAs). Yet,
a clear and rigorous definition of DOPs is lacking in the
Evolutionary Dynamic Optimization (EDO) community. In this
paper, we propose a unified definition of DOPs based on the
idea of multiple-decision-making discussed in the Reinforcement
Learning (RL) community. We draw a connection between
EDO and RL by arguing that both of them are studying
DOPs according to our definition of DOPs. We point out that
existing EDO or RL research has been mainly focused on some
types of DOPs. A unified benchmark problem, which is aimed
at the systematic study of various DOPs, is then developed.
Some interesting experimental studies on the benchmark reveal
that EDO and RL methods are specialized in certain types of
DOPs, and more importantly new algorithms for DOPs can
be developed by combining the strength of both EDO and RL
methods.},
	publisher = {IEEE Press},
	booktitle = {Congress on Evolutionary Computation}
}