{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/towards-a-general-purpose-belief-maintenance","title":"Towards a General-Purpose Belief Maintenance System","arxiv_id":"1304.3084","date":"2013-03-27","proceeding":null,"authors":["Brian Falkenhainer"],"abstract":"There currently exists a gap between the theories proposed by the probability\nand uncertainty and the needs of Artificial Intelligence research. These\ntheories primarily address the needs of expert systems, using knowledge\nstructures which must be pre-compiled and remain static in structure during\nruntime. Many Al systems require the ability to dynamically add and remove\nparts of the current knowledge structure (e.g., in order to examine what the\nworld would be like for different causal theories). This requires more\nflexibility than existing uncertainty systems display. In addition, many Al\nresearchers are only interested in using \"probabilities\" as a means of\nobtaining an ordering, rather than attempting to derive an accurate\nprobabilistic account of a situation. This indicates the need for systems which\nstress ease of use and don't require extensive probability information when one\ncannot (or doesn't wish to) provide such information. This paper attempts to\nhelp reconcile the gap between approaches to uncertainty and the needs of many\nAI systems by examining the control issues which arise, independent of a\nparticular uncertainty calculus. when one tries to satisfy these needs. Truth\nMaintenance Systems have been used extensively in problem solving tasks to help\norganize a set of facts and detect inconsistencies in the believed state of the\nworld. These systems maintain a set of true/false propositions and their\nassociated dependencies. However, situations often arise in which we are unsure\nof certain facts or in which the conclusions we can draw from available\ninformation are somewhat uncertain. The non-monotonic TMS 12] was an attempt at\nreasoning when all the facts are not known, but it fails to take into account\ndegrees of belief and how available evidence can combine to strengthen a\nparticular belief. This paper addresses the problem of probabilistic reasoning\nas it applies to Truth Maintenance Systems. It describes a belief Maintenance\nSystem that manages a current set of beliefs in much the same way that a TMS\nmanages a set of true/false propositions. If the system knows that belief in\nfact is dependent in some way upon belief in fact2, then it automatically\nmodifies its belief in facts when new information causes a change in belief of\nfact2. It models the behavior of a TMS, replacing its 3-valued logic (true,\nfalse, unknown) with an infinite valued logic, in such a way as to reduce to a\nstandard TMS if all statements are given in absolute true/false terms. Belief\nMaintenance Systems can, therefore, be thought of as a generalization of Truth\nMaintenance Systems, whose possible reasoning tasks are a superset of those for\na TMS.","url_abs":"http://arxiv.org/abs/1304.3084v1","url_pdf":"http://arxiv.org/pdf/1304.3084v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"towards-a-general-purpose-belief-maintenance","repo_url":"https://github.com/japoorv/biohacker-medikanren","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}