Titlebook: Case-Based Reasoning Research and Development; 19th International C Ashwin Ram,Nirmalie Wiratunga Conference proceedings 2011 Springer-Verl

沒(méi)有希望

Nonconvex Optimization and Its Applicationsadaptation methods, we demonstrate the effectiveness of a “l(fā)azier” approach to learning/problem solving in CBR that avoids commitment to previous adaptation paths and hence the need for feedback propagation.

ECG769

BIPED

虛構(gòu)的東西

Qualitative vs. Quantitative Plan Diversity in Case-Based Planningplanning method for obtaining qualitative plan diversity through the use of distance metrics which incorporate domain-specific content, without requiring a domain metatheory. To our knowledge, this is the first time qualitative plan diversity is being explored in a case-based planning context.

陳列

The 4 Diabetes Support System: A Case Study in CBR Research and Developmentamework for medical research as well as for artificial intelligence (AI) research. This new work has the potential to positively impact the health and wellbeing of patients with diabetes. This paper shares the 4DSS project experience.

輕而薄

Learning More from Experience in Case-Based Reasoningadaptation methods, we demonstrate the effectiveness of a “l(fā)azier” approach to learning/problem solving in CBR that avoids commitment to previous adaptation paths and hence the need for feedback propagation.

endure

ACTIN

Mathematical Fundamentals of Optimal Control out within T., a CBR system that searches cooking recipes satisfying constraints given by a user, or adapts recipes by substituting certain ingredients for others. The ingredient ontology of T. has been enriched thanks to ingredient properties extracted from recipe texts.

網(wǎng)絡(luò)添麻煩

顧客

Mathematical Fundamentals of Optimal Controlsing case-base coverage, including a new Monte-Carlo method for prediction early in case-base growth. It evaluates the performance of these approaches for three tasks: estimating competence, predicting the incremental benefit of acquiring new cases, and predicting the total number of cases required