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The set of states forms a graph where two states are connected if there is an operation that can be performed to transform the first state into the second. State space search often differs from traditional computer science search methods because the state space is implicit: the typical state space graph is much too large to generate and store ...
Vacuum World, a shortest path problem with a finite state space. In computer science, a state space is a discrete space representing the set of all possible configurations of a "system". [1] It is a useful abstraction for reasoning about the behavior of a given system and is widely used in the fields of artificial intelligence and game theory.
The state space or phase space is the geometric space in which the axes are the state variables. The system state can be represented as a vector , the state vector . If the dynamical system is linear, time-invariant, and finite-dimensional, then the differential and algebraic equations may be written in matrix form.
A directed graph. A classic form of state diagram for a finite automaton (FA) is a directed graph with the following elements (Q, Σ, Z, δ, q 0, F): [2] [3]. Vertices Q: a finite set of states, normally represented by circles and labeled with unique designator symbols or words written inside them
The system's evolving state over time traces a path (a phase-space trajectory for the system) through the high-dimensional space. The phase-space trajectory represents the set of states compatible with starting from one particular initial condition , located in the full phase space that represents the set of states compatible with starting from ...
In information technology and computer science, a system is described as stateful if it is designed to remember preceding events or user interactions; [1] the remembered information is called the state of the system. The set of states a system can occupy is known as its state space. In a discrete system, the state space is countable and often ...
In computer science, iterative deepening search or more specifically iterative deepening depth-first search [1] (IDS or IDDFS) is a state space/graph search strategy in which a depth-limited version of depth-first search is run repeatedly with increasing depth limits until the goal is found.
In the state space graph: the nodes are possible states, and the edges indicate reachability through a certain action. On the contrary, in Graphplan's planning graph: the nodes are actions and atomic facts, arranged into alternate levels, and the edges are of two kinds: from an atomic fact to the actions for which it is a condition, from an ...