James G. Schmolze

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KL-ONE is o system for representing knowledge in Artificial Intelligence progroms. It has been developed and refined over o long period ond hos been used in both basic research and implemented knowledge-based systems in o number of places in the Al community. Here we present the kernel ideas of KL-ONE, emphasizing its ability to form complex structured(More)
KL-ONE lets one define and use a class of descriptive terms called Concepts, where each Concept denotes a set of objects A subsumption relation between Concepts is defined which is related to set inclusion by way of a semantics for Concepts. This subsumption relation defines a partial order on Concepts, and KL-ONE organizes all Concepts into a taxonomy that(More)
Robots that plan to perform everyday tasks need knowledge of everyday physics. Physics For Robots (PFR) is a representation of part of everyday physics directed towards this need. It includes general concepts and theories, and it has been applied to tasks in cooking. PFR goes beyond most AI planning representation schemes by including natural processes that(More)
Partially observable Markov decision processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a convenient and efficient way. Representations built on logic allow for problems to be specified in a compact and transparent manner. Moreover, decision making algorithms can(More)
BBN's project in Knowledge Representation for Natural Language Understanding is developing techniques for computer assistance to a decision maker who is collecting information about and making choices in a complex situation. In particular, we are designing a system for natural language control of an intelligent graphics display. This system is intended for(More)