Author/Editor		Todorovski, Ljupčo; Džeroski, Sašo
Title		Declarative bias in equation discovery
Type		članek
Source		In: Fisher DH Jr, editor. Machine learning. Proceedings of the 14th international conference (ICML'97); 1997 Jul 8-12; Nashville. San Francisco: Morgan Kaufmann publishers,
Publication year		1997
Volume		str. 376-84
Language		eng
Abstract		Declarative bias plays an important role when learning in potentially huge hypothesis spaces. While scientific discovery systems, which perform equation discovery as a subtask, consider such potentially huge hypothesis spaces, few (if any) employ declarative (as opposed to hard-coded) bias to define and restrict their hypothesis space. We present an equation discovery system LAGRAMGE that uses grammars to define and restrict its hypothesis space. These grammars can make use of functions defined as domain specific knowledge, in addition to common mathematical operators. LAGRAMGE was successfully applied to three artificial domains, rediscovering the correct equations. It was also applied to a real-world problem, discovering equations that make sense in terms of domain knowledge and produce accurate predictions.
Descriptors		ARTIFICIAL INTELLIGENCE SOFTWARE ECOSYSTEM ZOOPLANKTON PHYTOPLANKTON COMPUTER-ASSISTED INSTRUCTION POPULATION DYNAMICS MODELS, THEORETICAL FRESH WATER