Machine Learning and Planning for Data Management in Forestry

Authors:
Stan Matwin;Daniel Charlebois;David G. Goodenough;Pal Bhogal
Affiliations:
-;-;-;-
Venue:
IEEE Expert: Intelligent Systems and Their Applications
Year:
1995

Citing 5
Cited 0

Logical foundations of artificial intelligence

Logical foundations of artificial intelligence
Case-based planning: viewing planning as a memory task

Case-based planning: viewing planning as a memory task
Theory and algorithms for plan merging

Artificial Intelligence
Learning by analogical reasoning in general problem-solving

Learning by analogical reasoning in general problem-solving
Training agents in a complex environment

CAIA '95 Proceedings of the 11th Conference on Artificial Intelligence for Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

Seidam uses a planning-based approach that combines three problem-solving methods-transformational analogy, derivational analogy, and goal regression-to automatically answer forest-management queries.