A5023283817- AI-based Problem Solving and Planning
- Semantic Web and Ontologies
- Logic, Reasoning, and Knowledge
- Computability, Logic, AI Algorithms
- Biomedical Text Mining and Ontologies
- Artificial Intelligence in Games
- Evolutionary Algorithms and Applications
- Data Quality and Management
- Topic Modeling
- Logic, programming, and type systems
- Model-Driven Software Engineering Techniques
- Engineering and Information Technology
- Teaching and Learning Programming
- Neural Networks and Applications
- Explainable Artificial Intelligence (XAI)
- Scientific Computing and Data Management
- Ethics and Social Impacts of AI
- Advanced Database Systems and Queries
- Bayesian Modeling and Causal Inference
- Natural Language Processing Techniques
- Constraint Satisfaction and Optimization
- Complex Systems and Decision Making
- Multi-Agent Systems and Negotiation
- Business Process Modeling and Analysis
- Distributed and Parallel Computing Systems
Cycorp (United States)
1995-2022
McLennan Community College
1989-2003
Stanford University
1979-1993
Balcones Technologies (United States)
1989-1993
Yale University
1990
Carnegie Mellon University
1977-1984
Laboratoire d'Informatique de Paris-Nord
1980-1984
Palo Alto University
1983
Reading,Mass.: Addison-Wesley Pub., 1983. 1: include bibliography: p. 405-420 -- (Teknowledge Series in Knowledge Engineering. Hayes-Roth, Frederick, series editor). This book is a collaboration of 38 expert system researchers and developers. It provides broad introduction to the concepts methods necessary for an understanding how these systems work
Since 1984, a person-century of effort has gone into building CYC, universal schema roughly 10 5 general concepts spanning human reality. Most the time been spent codifying knowledge about these concepts; approximately 6 commonsense axioms have handcrafted for and entered CYC's base, millions more inferred cached by CYC. This article examines fundamental assumptions doing such large-scale project, reviews technical lessons learned developers, surveys range applications that are or soon will...
Cyc is a bold attempt to assemble massive knowledge base (on the order of 10 8 axioms) spanning human consensus knowledge. This article examines need for such an undertaking and reviews authos' efforts over past five years begin its construction. The methodology history project are briefly discussed, followed by more developed treatment current state representation language used (epistemological level), techniques efficient inferencing default reasoning (heuristic content organization base.
After explicating the need for a large commonsense knowledge base spanning human consensus knowledge, we report on many of lessons learned over first five years attempting its construction. We have come long way in terms methodology, representation language, techniques efficient inferencing, ontology base, and environment infrastructure which is being built. describe evolution Cyc current state close with look at our plans expectations coming years, including an argument how why project...
article Free Access Share on Enabling agents to work together Authors: R. V. Guha Microelectronics and Computer Technology Corp., Austin, TX TXView Profile , Douglas B. Lenat Authors Info & Claims Communications of the ACMVolume 37Issue 7July 1994 pp 126–142https://doi.org/10.1145/176789.176804Online:01 July 1994Publication History 97citation767DownloadsMetricsTotal Citations97Total Downloads767Last 12 Months9Last 6 weeks2 Get Citation AlertsNew Alert added!This alert has been successfully...
Abstract Knowledge graphs (KGs) have emerged as a compelling abstraction for organizing the world's structured knowledge and integrating information extracted from multiple data sources. They are also beginning to play central role in representing by AI systems, improving predictions of systems giving them expressed KGs input. The goals this article (a) introduce discuss important areas application that gained recent prominence; (b) situate context prior work AI; (c) present few contrasting...
Abstract After explicating the need for a large common-sense knowledge base spanning human consensus knowledge, we report on many of lessons learned over first five years attempting its construction. We have come long way, in terms methodology, representation language, techniques efficient inferencing, ontology base, and environment infrastructure which it is being built. describe evolution Cyc, current state, close with look ahead at our plans expectations coming years, including an...