Hill-climbing is a figure of speech for methods designed to reach the top (best) place in a solution space while only selecting or scheduling actions that contribute positively to improving the solution. For example, one can hope to maximize the objective function value of a problem by only making decisions (moves through the solution space) that improve the value of the function. One can also hope to minimize the objective function value of a problem by only making decisions that reduce the value of the function. One distinction between this type of search process and others that follow in this book is the strict adherence to the acceptance of moves or actions in the correct direction. Other search processes that follow in this book may allow deviations from this rule, often with the idea that one may need to break free from local optima by accepting inferior moves or actions during a search process. This course of action is unavailable with strict hill-climbing search processes.