Qualitative reasoning: modeling and simulation with incomplete knowledge
Qualitative reasoning: modeling and simulation with incomplete knowledge
Advances in the Dempster-Shafer theory of evidence
Fast discovery of association rules
Advances in knowledge discovery and data mining
Rough mereology in information systems with applications to qualitative spatial reasoning
Fundamenta Informaticae - Special issue on Concurrency specification and programming (CS&P)
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough-Neuro-Computing: Techniques for Computing with Words
Rough-Neuro-Computing: Techniques for Computing with Words
Rough Sets: Mathematical Foundations
Rough Sets: Mathematical Foundations
COSIT '99 Proceedings of the International Conference on Spatial Information Theory: Cognitive and Computational Foundations of Geographic Information Science
Repräsentation und Verarbeitung räumlichen Wissens
Repräsentation und Verarbeitung räumlichen Wissens
Atomicity vs. Infinite Divisibility of Space
COSIT '99 Proceedings of the International Conference on Spatial Information Theory: Cognitive and Computational Foundations of Geographic Information Science
Calculi for Qualitative Spatial Reasoning
AISMC-3 Proceedings of the International Conference AISMC-3 on Artificial Intelligence and Symbolic Mathematical Computation
On Connection Synthesis via Rough Mereology
Fundamenta Informaticae - Qualitative Spatial Reasoning
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
| Hi-index | 0.00 |
The term rough inclusion was introduced as a generic term by Polkowski and Skowron in the seminal paper that laid foundations for Rough Mereology – a paradigm for Approximate Reasoning that combines ideas of Mereology – a set theory based on the notion of a part – with ideas of Rough Set Theory and Fuzzy Set Theory; in particular, its basic predicate of rough inclusion is a rendering of the notion of being a part to a degree. Rough Mereology is an approach towards constructing reasoning schemes that take into account uncertainty of either knowledge or concepts used in reasoning. This abstract reasoning methodology is therefore a constituent of the vast field of Cognitive Technologies (styled also Artificial Intelligence). It is well–known that mereological theories of objects have been applied in Spatial Reasoning – reasoning about uncertainty in spatial contexts. The majority of theories based on mereology and applied in reasoning about spatial objects stem from the idea of A. N. Whitehead, viz., Mereology Theory based on the predicate of being connected. In this article, we give a survey of the current state of the art in spatial reasoning based on constructs of Rough Mereology. We include here theoretical results – some of them already shown in earlier works – that witness applicability of constructs based on rough inclusions in spatial reasoning as well as we mention recent works on practical applications to real–world robot navigation.