@inbook{39480cc5b21e44db8a1135e5f535edcc,
title = "Modelling inertia in action languages",
abstract = "Logic-based approaches to reasoning about actions, change and causality, highlight efficient representation and processing of domain background knowledge as an important task. Action theories recently developed in the framework of action languages with inertia and ramifications [20,14] not only adopt the principle of minimal change reinforced with the policy of categorisation (assigning different degrees of inertia to language elements) but also try to incorporate background causal knowledge. In this paper we aim to trace the evolution of action languages and to explore interactions between ontological characteristics of action domains such as inertia and causality. Such an analysis should clarify how possible solutions to the frame and the ramification problems are affected by applying the policy of categorisation to causal' domains. We first attempt to identify conditions (more precisely, restrictions) which preserve the meaning of domain descriptions when moving among various analysed languages. Relaxing such restrictions can help in evaluating the role of the frame concept (and policy of categorisation, in general) in an action language with fluent-triggered causality.",
author = "Mikhail Prokopenko and Pavlos Peppas",
year = "1998",
doi = "10.1007/3-540-64413-X_39",
language = "English",
isbn = "9783540644132",
series = "Lecture Notes in Computer Science",
publisher = "Springer, Springer Nature",
pages = "234--247",
editor = "Grigoris Antoniou and Ghose, {Aditya K.} and Miros{\l}aw Truszczy{\'n}ski",
booktitle = "Learning and Reasoning with Complex Representations",
address = "United States",
note = "Workshops on Reasoning with Incomplete and Changing Information and on Inducing Complex Representations, PRICAI 1996 ; Conference date: 26-08-1996 Through 30-08-1996",
}