Nonmonotonic logic

• Authors: Thomas Sudkamp
• Venue: Encyclopedia of Computer Science
• Year: 2003

A major goal of artificial intelligence is the development of automated agents that are capable of making decisions, responding to the actions of others, and determining the consequences of their own actions. In order to achieve this behavior, these agents must have access to information describing the objects in the environment and the relationships of the objects to each other and to the agent itself. Much of the pioneering work in artificial intelligence used the predicate calculus as a language for representing and analyzing domain information. Unfortunately, the predicate calculus does not have the flexibility to perform many types of inference required for common sense reasoning. A fundamental property of the predicate calculus is that the acquisition of new information preserves previous conclusions. Any system in which the set of conclusions grows with the addition of information is said to be monotonic.