Artificial Intelligence
Artificial Intelligence
Reasoning with worlds and truth maintenance in a knowledge-based programming environment
Communications of the ACM
Artificial Intelligence
Proceedings of the 2nd international workshop on Non-monotonic reasoning
AI Magazine - Reports from three of the 1990 Spring symposia and eight workshops held over the past two years
A general framework for reason maintenance
Artificial Intelligence
SSDBM '96 Proceedings of the Eighth International Conference on Scientific and Statistical Database Management
Finding all justifications of OWL entailments using TMS and MapReduce
Proceedings of the 20th ACM international conference on Information and knowledge management
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Truth maintenance (also called belief revision or reason maintenance) is an area of AI concerned with revising sets of beliefs and maintaining the truth in the system when new information contradicts existing information. Truth maintenance systems (TMSs) work with inference engines that act as problem solvers within large search spaces. The inference engine explores alternatives, makes choices, and examines the consequences of the choices. If a contradiction is detected during this process, the TMS eliminates it by revising the knowledge base. Together, the TMS and inference engine can solve problems where algorithmic solutions don't exist, and thus offer an efficient way to deal with search spaces that are large due to combinatorial explosions of alternatives. TMSs can be implemented either explicitly in search problem solving tools, or implicitly within applications that solve particular search problems. All applications that solve search problems have something in common that can be extracted and implemented within a tool. This tool can then solve new problems without programming everything from scratch.