One of the fundamental skills of intelligence is planning. Generally, planning is described as finding sequences of actions to satisfy one or more goals. Despite its importance, the process of planning is not well understood. This has lead to a number of attempts to mimic the planning process with computer based experiments. These Artificial Intelligence planners use various algorithms to approach a fundamental set of planning problems.
By their nature, planning problems are defined using goal states. If there is a single goal, the problem is often simple. Planning for multiple goals is also simple if the goals are completely independent. Some goals must be satisfied in a particular order; this occurs when they are independent but ordered. The most complex case arises when a number of goals must be satisfied simultaneously (this is non-linear planning; all other cases are linear).
To move between a start and goal state, operators are applied. The choices and orders of operators are both major concerns. A great deal of work has been done for selecting operators and choosing their order, but problems of complexity still tend to overwhelm most planning methods.