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Active Logics: A Unified Formal Approach to Episodic Reasoning

dc.contributor.authorElgot-Drapkin, Jenniferen_US
dc.contributor.authorKraus, Sariten_US
dc.contributor.authorMiller, Michaelen_US
dc.contributor.authorNirkhe, Madhuraen_US
dc.contributor.authorPerlis, Donalden_US
dc.date.accessioned2004-05-31T23:00:21Z
dc.date.available2004-05-31T23:00:21Z
dc.date.created1999-10en_US
dc.date.issued1999-10-14en_US
dc.identifier.urihttp://hdl.handle.net/1903/1039
dc.description.abstractArtificial intelligence research falls roughly into two categories: formal and implementational. This division is not completely firm: there are implementational studies based on (formal or informal) theories (e.g., CYC, SOAR, OSCAR), and there are theories framed with an eye toward implementability (e.g., predicate circumscription). Nevertheless, formal/theoretical work tends to focus on very narrow problems (and even on very special cases of very narrow problems) while trying to get them ``right'' in a very strict sense, while implementational work tends to aim at fairly broad ranges of behavior but often at the expense of any kind of overall conceptually unifying framework that informs understanding. It is sometimes urged that this gap is intrinsic to the topic: intelligence is not a unitary thing for which there will be a unifying theory, but rather a ``society'' of subintelligences whose overall behavior cannot be reduced to useful characterizing and predictive principles. Here we describe a formal architecture that is more closely tied to implementational constraints than is usual for formalisms, and which has been used to solve a number of commonsense problems in a unified manner. In particular, we address the issue of formal, integrated, and longitudinal reasoning: inferentially-modeled behavior that incorporates a fairly wide variety of types of commonsense reasoning within the context of a single extended episode of activity requiring keeping track of ongoing progress, and altering plans and beliefs accordingly. Instead of aiming at optimal solutions to isolated, well-specified and temporally narrow problems, we focus on satisficing solutions to under-specified and temporally-extended problems, much closer to real-world needs. We believe that such a focus is required for AI to arrive at truly intelligent mechanisms with the ability to behave effectively over considerably longer time periods and range of circumstances than is common in AI today. While this will surely lead to less elegant formalisms, it also surely is requisite if AI is to get fully out of the blocks-world and into the real world. (Also cross-referenced as UMIACS-TR-99-65)en_US
dc.format.extent683416 bytes
dc.format.mimetypeapplication/postscript
dc.language.isoen_US
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-4072en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-99-65en_US
dc.titleActive Logics: A Unified Formal Approach to Episodic Reasoningen_US
dc.typeTechnical Reporten_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US


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