Explanation-based learning with analogy for impasse resolution. (1st November 2016)

• Record Type: Journal Article
• Authors: Timperley, Matt; Mokhtar, Maizura; Bellaby, Gareth; Howe, Joe
• Is Part Of: Expert systems with applications. Volume 61(2016)
• Page Start: 181
• Page End: 191
• Publication Date: 2016-11-01
• Subjects: Explanation-based learning -- Impasse resolution -- Analogy; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2016.05.030
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: A method for including analogical reasoning with EBL is presented. Analogy is proposed as a method for impasse resolution. Extension of domain theory using analogy shown to cater for modular platforms. Abstract: This paper proposes an algorithm for the inclusion of analogy into Explanation-Based Learning (EBL). Analogy can be used when an impasse is reached to extend the deductive closure of EBL's domain theory. This enables the generation of control laws, via EBL, for hardware which is not catered for in the domain theory. This advantage addresses a problem which represents a dearth in the current literature. Integrated Modular Avionics (IMA) literature has thus far been concerned with the architectural considerations. This paper seeks to address the impact of hardware changes on the controllers within an IMA architecture. An algorithm is proposed and applied to control an aviation platform with an incomplete domain theory. Control rules are generated when no deductive explanations are possible, which still reflect the intent of the domain theory.