Basic Components of a Planning System
When a particular problem will be solved, at that time some specific rules regarding to that problem are to be applied. Then apply the choosen rule to compute the new problem state that arises from its application. Detect when a solution has been found and calculate the active and inactive ends of that problem. Various components of a planning system are described as follows.
(a) States: For a planning process, the planners decompose the world into some environments. Then environments are defined by some logical conditions and states. The problems can be viewed as the task of finding a path from a given starting state to some desirable goal state. The state can be viewed as a conjunction of positive literals. For example, Rich A famous might represent the state of a best agent.
(b)Goal: A goal is a specified state. To find a solution to a problem using a search procedure is to generate moves through the problem space until a goal state is reached. In the context of game playing programs, a goal state is one in which we win. Unfortunately, for interesting games like chess, it is not usually, possible, even with a good plausible move generator, to search until a goal state is found.
(c) Actions: An action is specified en terms of the pre-conditions that must hold before it can be executed and then the effects that ensue when it is executed. For example, an action for running a ActiontigerfromRunoneT,locationfrom,to,another is
(d)Precondition: The precondition is a conjunction of function free positive literals stating what must be true in a state before the action can be executed.
(e) Effect: It is a conjunction of function free literals describing how the state changes when the action is executed.
(f) Finding a solution: A planning system has succeeded in finding a solution to a problem when it has found a sequence of operators that transforms the initial problem state into the goal state. The way it can be solved depends on the way that state descriptions are represented.
(g) Calculating the Dead State: As a planning system is searching for a sequence of operators to solve a particular problem, it must be able to detect when it is exploring a path that can never lead to a solution. The same reasoning methods that can be used to detect a solution can often be used for detecting a dead path. If the search process is reasoning in forward direction from the initial state, it can prune any path that leads to a state from which the goal state cannot be reached. If the search process is reasoning backward from the goal state, it can also terminate a path either because it is sure that the starting state cannot be reached.