Authors:
Alexander Brodsky
and
Juan Luo
Affiliation:
George Mason University, United States
Keyword(s):
Decision Support, Decision Guidance, Decision Optimization, Machine Learning, Data Management, Decision Analytics.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Group Decision Support Systems
;
Query Languages and Query Processing
;
Strategic Decision Support Systems
Abstract:
Decision guidance systems are a class of decision support systems that are geared toward producing actionable recommendations, typically based on formal analytical models and techniques. This paper proposes the Decision Guidance Analytics Language (DGAL) for easy iterative development of decision guidance systems. DGAL allows the creation of modular, reusable and composable models that are stored in the analytical knowledge base independently of the tasks and tools that use them. Based on these unified models, DGAL supports declarative queries of (1) data manipulation and computation, (2) what-if prediction analysis, (3) deterministic and stochastic decision optimization, and (4) machine learning, all through formal reduction to specialized models and tools, and in the presence of uncertainty.