摘要：the last few decades significant progress has been made in the area of spatial and temporal reasoning. There is a growing interest in this area, especially within the artificial intelligence community, which may be attributed to the large number of application domains in which one has to deal directly or indirectly with temporal or spatial information, or both. However, dealing with time and space is not restricted to artificial intelligence. The analysis of concurrent programs, for example, faces difficult temporal questions, while the design of complex hardware for modern computing machines is plagued by spatial problems. Geographic information systems, tracking systems, mobile networks, distributed systems, cooperating autonomous agents, distributed databases, planning, robot motion, and many other complex systems challenge the capabilities of existing knowledge representation methods and reasoning techniques. Even long-standing research areas such as natural language understanding and production line management are brimming with unanswered questions about the interpretation and control of time and space. There is a large body of methods and techniques to attack problems involving space and time, including non-monotonic and modal logics, circumscription methods, chronological minimization methods, relation algebras, and applications of constraint-based reasoning.
