Showing papers on "Qualification problem published in 1996"
Proceedings Article•
5 Nov 1996
TL;DR: This work proposes to incorporate causality by treating the proposition that an action is qualified as a fluent which is initially assumed away by default but otherwise potentially indirectly affected by the execution of actions.
Abstract: In formal theories for reasoning about actions, the qualification problem denotes the problem to account for the many conditions which, albeit being unlikely to occur, may prevent the successful execution of an action. By a simple counter-example in the spirit of the well-known Yale Shooting scenario, we show that the common straightforward approach of globally minimizing such abnormal disqualifications is inadequate as it lacks an appropriate notion of causality. To overcome this difficulty, we propose to incorporate causality by treating the proposition that an action is qualified as a fluent which is initially assumed away by default but otherwise potentially indirectly affected by the execution of actions. Our formal account of the qualification problem includes the proliferation of explanations for surprising disqualifications and also accommodates so-called miraculous disqualifications. We moreover sketch a version of the fluent calculus which involves default rules to address abnormal disqualifications of actions, and which is provably correct wrt. our formal characterization of the qualification problem. In L. C. Aiello and J. Doyle and S. Shapiro, editors, Proc. of the International Conference on Principles of Knowledge Representation and Reasoning, pages 51–62, Cambridge, MA, 1996. Morgan Kaufmann
21 citations
TL;DR: A new method which uses the stratified ATMS for reasoning about action to overcome the limitations of existing approaches to solve the frame problem, qualification problem and the ramification problem.
Abstract: Reasoning about action is an important aspect of common sense reasoning and planning. It gives rise to three classical problems: the frame problem, the qualification problem and the ramification problem. Existing approaches cannot deal with these problems efficiently. This paper presents a new method which uses the stratified ATMS for reasoning about action to overcome the limitations of these approaches.
2 citations
1 Nov 1996
TL;DR: This paper incorporates the assumptions that are inherent to both the frame and the qualification problem into the semantics of Dynamic Logic by defining preferences over Dynamic logic models and gives an intended semantics that, for each declarative action specification, selects a unique meaning for each action.
Abstract: In this paper we investigate minimal semantics for Propositional Dynamic Logic formulas. The goal is to be able to write action specifications in a declarative pre/post condition style. The declarative specification of actions comes with some well known problems: the frame problem, the qualification problem and the ramification problem. We incorporate the assumptions that are inherent to both the frame and the qualification problem into the semantics of Dynamic Logic by defining preferences over Dynamic logic models. This gives us an intended semantics that, for each declarative action specification, selects a unique meaning for each action.
2 citations
26 Aug 1996
TL;DR: This paper studies a hybrid neural-symbolic belief representation system called Neural-Logic Belief Network (NLBN) where IF-THEN rules can be more realistically captured for commonsense reasoning.
Abstract: In commonsense reasoning, conditional statements of the form "IF condition(s) THEN conclusion(s)" are the most common and important constructions. While material implication is generally used in classical logic based belief representation systems, its dual implication could be semantically too strong for expressing commonsense IF-THEN rules because not all contributing conditions of a rule can be expressed (the Qualification Problem [18]) and the negation of conclusions do not always imply the negation of the conditions. This paper studies a hybrid neural-symbolic belief representation system called Neural-Logic Belief Network (NLBN) [14] where IF-THEN rules can be more realistically captured for commonsense reasoning. Deduction of an IF-THEN rule in this formalism is considered as information flow from the condition(s) to the conclusion(s). In this system, the strength of conclusions can be modeled by using individual rule mapping functions.
1 citations