Why AM and EURISKO Appear to Work
Explore this paper's citation graph
Summary
The am program was constructed by Lenat in 1975 as an early experiment in getting machines to learn by discovery, and it is seen that the difficulties they cite fall into four categories, the most serious of which are omitted heuristics and miscommunications.
- Type
- article
- Published
- 1984-07-27
- Cited by
- 350
- References
- 16
- Access
- Open access
- OpenAlex
- https://openalex.org/W48479683
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:1800673
Keywords
Heuristics, Computer science, Artificial intelligence, Vocabulary, Meaning (existential)
References
- Theory Formation by Heuristic Search
- A Representation Language Language
- Foundations of Envisioning
- RLL-1: A Representation Language Language
- Progress report on program-understanding systems.
- Building expert systems
- Competitive Argumentation in Computational Theories of Cognition.
- AM, an artificial intelligence approach to discovery in mathematics as heuristic search
- The Nature of Heuristics
- BEINGS: Knowledge as Interacting Experts
- Realization of a geometry theorem proving machine
Cited by
- Substantial Constructive Induction Using Layered Information Compression: Tractable Feature Formation in Search
- Concepts and Autonomous Agents
- Machine discovery of effective admissible heuristics
- Use of Domain Knowledge in Constructive Induction
- Survey on special purpose computer architectures for AI
- Il: an artificial intelligence approach to theory formation in mathematics
- Learning and representation: Tensions at the interface
- Conflict-Oriented Requirements Restructuring
- Computational Creativity: Three Generations of Research and Beyond
- Beyond the metaphor
- Algorithm Synthesis: A Comparative Study
- EUCLID: A System for the Exploratory Discovery of Geometrical Properties of Triangles
- On the Discovery of Mathematical Theorems
- Artificial Intelligence in Music Education: A Critical Review
- A Framework for Autonomously Performing Knowledge Discovery In Databases
- Neural trust model for multi-agent systems
- Constructive Induction on Domain Information
- The problem of storing common sense in artificial intelligence. Context in cyc
- Learning to Learn Decision Trees
- Intentional systems and the artificial intelligence (ai) hermeneutic network: agency and intentionality in expressive computational systems