Dynamic Spatial Reasoning Based on Action

doi:10.3969/j.issn.1006-2475.2018.03.003

Abstract

Abstract: Dynamic spatial relations representation and reasoning have always been a focus of research in qualitative spatial reasoning. In this paper, the qualitative spatial relation of spatial primitive area is represented by rectangle relation. Some elaboration and extension are made for dynamic spatial system defined by Bhatt. Eight moving actions are defined for spatial entity, and the state transition graph and the state transition table are given under different actions for interval relation in spatial situation with multiple spatial entities. A tuple is used to formalize spatial situation, a basic missions is defined in dynamic spatial system, what the new spatial situation is when an entity takes action in the history situation. The method to solve the missions is given, and the limitation and shortages of the method are also presented. Furthermore, an application situation is given in this paper.

Key words: dynamic spatial system, spatial reasoning, spatial situation, action, state transition graph

CLC Number:

TN182

XIE Yu-mei1, GAO Hai-yan2. Dynamic Spatial Reasoning Based on Action[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2018.03.003.

References

［1］ Bhatt M, Loke S. Modelling dynamaic spatial systems in the situation calculus［J］. Spatial Cognition and Computation, 2008,8(1-2):86-130.
［2］ Bhatt M, Guesgen H, Wolfl S, et al. Qualitative spatial and temporal reasoning: Emerging applications,trends,and directions［J］. Spatial Cognition & Computation, 2011,11(1):1-14.
［3］ Freksa C. Conceptual neighborhood and its role in temporal and spatial reasoning［M］// Decision Support Systems and Qualitative Reasoning. 1991:181-187.
［4］ Egenhofer M J, Al-Taha K K. Reasoning about gradual changes of topological relationships［M］// Theories and Methods of Spatio-temporal Reasoning in Geographic Space. 1992:196-219.
［5］ Rajagoplan R. A model for integrated qualitative spatial and dynamic reasoning about physical systems［C］// Proceedings of the 12th National Conference on Artificial Intelligence(AAAI-94). 1994:1411-1417.
［6］ Dylla F, Moratz R. Exploiting qualitative spatial neighborhoods in the situation calculus［C］// Proceedings of the 4th International Conference on Spatial Cognition IV Reasoning, Action, Interaction. 2004:304-332.
［7］ Bhatt M, Rahayu W, Sterling G. Qualitative spatial reasoning with topological relations in the situation calculus［C］// Proceedings of the 19th International Florida Artificial Intelligence Research Society Conference. 2006:713-718.
［8］ Delafontaine M, Weghe N V D, Bogaert P， et al. Qualitative relations between moving objects in a network changing its topological relations［J］. Information Sciences, 2008,178(8):1997-2006.
［9］ Bhatt M. Reasoning about Space, actions, and change: A paradigm for applications of spatial reasoning［M］// Qualitative Spatio-temporal Representation and Reasoning: Trends and Future Directions. 2012:284-320.
［10］Bhatt M. Commonsense inference in dynamic spatial systems: Epistemological requirements［C］// The 23rd International Florida Artificial Intelligence Research Society Conference (FLAIRS 2010). 2010:3-20.
［11］Suchan J, Bhatt M, Schultz C. Deeply semantic inductive spatio-temporal learning［C］// The 26th International Conference on Inductive Logic Programming. 2016:73-80.
［12］Waga P A, Bhatt M, Schultz C. ASPMT(QS): Non-monotonic spatial reasoning with answer set programming modulo theories［C］// Proceedings of the 13th International Conference on Logic Programming and Nonmonotonic Reasoning. 2015:488-501.
［13］梁晶晶. 空间推理中多种空间关系结合和时空变化的研究［D］. 西安:西安交通大学， 2011．
［14］Song Xiaohua, Quyang Dantong. Automated planning method for dealing with dynamic spatial relations［J］. Journal of Software, 2012,23(10):2564-2571.
［15］杨帅. 动态空间中运动区间与静止区间统一表达模型的研究［D］. 长春:吉林大学, 2014.
［16］Zhou Yan, Wang Zhe, He Di. Spatial-temporal reasoning of Geovideo data based on ontology［C］// 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). 2016:4470-4473.
［17］Bhatt M, Guesgen H, Hazarika S. Proceedings of the workshop on Spatio-Temporal dynamics(STeDy)［C］// IJCAI 2015: International Joint Conference on Artificial Intelligence(Buenos Aires, Argentina). 2015.

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