An iterative algorithm of local search that starts with an arbitrary solution to a problem, then attempts to find a better solution by making an incremental change to the solution. If the change produces a better solution, another incremental change is made to the new solution, and so on until no further improvements can be found. There are several variants of the algorithm, e.g.:
- Simple hill-climbing
- Steepest ascent hill-climbing
- Stochastic hill-climbing
Purely gradient strategy has a basic disadvantage typical for all gradient methods – it may reach a local extreme only.
An example: Order in which the nodes are expanded (a path from S to M)