Cellular Transport Systems Improved: Achieving Efficient Operations with Answer Set Programming

Schieweck, Steffen; Kern-Isberner, Gabriele; Hompel, Michael ten

doi:10.1007/978-3-030-16469-0_16

Cited by 1 publication

(1 citation statement)

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“…Answer set programming (ASP, (Baral 2010;Gelfond and Lifschitz 1988;Gelfond 2008)) is a well-established knowledge representation and reasoning (KR) formalism which has found its way into many application domains (Takeuchi et al 2023;Abels et al 2021;Gebser et al 2018;Schieweck, Kern-Isberner, and ten Hompel 2017). As a most important feature of ASP, default negation (Clark 1977) allows for reasoning with rules such as "B ← A, not C." stating that if A holds, then B follows unless C is proven to be true, even if specific information on the default-negated literal C is not available.…”

Section: Introductionmentioning

confidence: 99%

Prioritizing Answer Sets Based on Conditional Expert Knowledge

Wilhelm

Thevapalan

Kern-Isberner

2023

FLAIRS

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Answer set programming (ASP) and conditional reasoning both are powerful and widely used methodologies from the field of knowledge representation and reasoning (KR) which are capable of formalizing default statements that usually hold but also leave room for exceptions. While ASP convinces with an intuitive rule-based syntax and fast solvers, conditionals come along with a sophisticated preference-based semantics. Here, we combine both approaches by calculating answer sets which we then prioritize based on conditional expert knowledge. We apply our hybrid approach to the task of planning warehouse layouts from the logistics domain which is predestinated for our approach because it involves, on the low-level, many variables and technical framework conditions (like rack positions) and, on the high-level, expert knowledge of the layout designer.

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