Spatial Decision Support Knowledge Portal

Stochastic

A stochastic process is one whose behavior is non-deterministic in that a state does not fully determine its next state. Classical examples of this are medicine: a doctor can administer the same treatment to multiple patients suffering from the same symptoms, but the patients may not all react to the treatment the same way. This makes medicine a stochastic process. Additional examples are warfare and rhetoric, where the successes and failures cannot be predicted with certainty. In artificial intelligence, stochastic programs work by using probabilistic methods to solve problems, as in simulated annealing, neural networks, stochastic optimization, and genetic algorithms. A problem itself may be stochastic as well, as in planning under uncertainty. A deterministic environment is much simpler for an agent to deal with. An example of a stochastic process in the natural world is pressure in a gas. Even though (classically speaking) each molecule is moving in a deterministic path, the motion of a collection of them is computationally and practically unpredictable. A large enough set of molecules will exhibit stochastic characteristics, such as filling the container, exerting equal pressure, diffusing along concentration gradients, etc. These are emergent properties of the system.

Graphical Ontology Browser

• Click on a node to jump to the content of that node
• Pan to see the rest of the graph
• Scroll the mousewheel up and down to zoom in and out
• Rearrange the nodes in the graph by dragging a node to a different position

References