Experimenting and theorizing in theory formation
ISMIS '86 Proceedings of the ACM SIGART international symposium on Methodologies for intelligent systems
Scientific discovery: computational explorations of the creative process
Scientific discovery: computational explorations of the creative process
A robust approach to numeric discovery
Proceedings of the seventh international conference (1990) on Machine learning
Using domain knowledge to aid scientific theory revision
Proceedings of the sixth international workshop on Machine learning
Conflict Resolution as Discovery in Particle Physics
Machine Learning
Determining repeatability and error in experimental results by a discovery system
Methodologies for intelligent systems, 5
The right representation for discovery: finding the conservation of momentum
ML92 Proceedings of the ninth international workshop on Machine learning
A symbolic algorithm for computing coefficients' accuracy in regression
ML92 Proceedings of the ninth international workshop on Machine learning
Determining Arguments of Invariant Functional Descriptions
Machine Learning
Chemical Discovery as Belief Revision
Machine Learning
Introduction: Cognitive Autonomy in Machine Discovery
Machine Learning
An Integrated Framework for Empirical Discovery
Machine Learning
Discovery as Autonomous Learning from the Environment
Machine Learning
The Design of Discrimination Experiments
Machine Learning
Rough Sets and Knowledge Discovery: An Overview
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
Automated discovery in a chemistry laboratory
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
Discovery of equations: experimental evaluation of convergence
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Operational definition refinement: a discovery process
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Learning engineering models with the minimum description length principle
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Scientific model-building as search in matrix spaces
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
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We define the problem of empirical search for knowledge by interaction with a setup experiment, and we present a solution implemented in the FAHRENHEIT discovery system. FAHRENHEIT autonomously explores multi-dimensional empirical spaces of numerical parameters, making experiments, generalizing them into empirical equations, finding the scope of applications for each equation, and setting new discovery goals, until it reaches the empirically complete theory. It turns out that a small number of generic goals and a small number of data structures, when combined recursively, can lead to complex discovery processes and to the discovery of complex theories. We present FAHRENHEIT's knowledge representation and the ways in which the discovery mechanism interacts with the emerging knowledge. Brief descriptions of several real-world applications demonstrate the system's discovery potential.