A significant number of qualitative methods for representing and reasoning about spatial and temporal information have now been developed that address limitations of purely numerical approaches. Despite this, qualitative spatial and temporal reasoning (QSTR) is yet to be fully utilised by researchers and software developers outside the QSTR community. In our view, the problem is that in many ca...

Ever since Allen introduced his qualitative interval algebra in 1983, the area of qualitative spatial and temporal reasoning (QSTR) has been motivated by potential application areas that require humanoriented, commonsense reasoning. Despite this, it is well recognised in the community that there are relatively few commercial applications that heavily employ QSTR calculi. In this paper we direct...

About two decades ago, the field of Qualitative Spatial and Temporal Reasoning (QSTR) emerged as a new area of AI research that set out to grasp human-level understanding and reasoning about spatial and temporal entities, linking formal approaches to cognitive theories. Empowering artificial agents with QSTR capabilities is claimed to facilitate manifold applications, including robot navigation...

Although a wide range of sophisticated Qualitative Spatial and Temporal Reasoning (QSTR) formalisms have now been developed, there are relatively few applications that apply these commonsense methods. To address this problem, the authors of this chapter developed methodologies that support QSTR application design. They established a theoretical foundation for QSTR applications that includes the...

Reasoning about spatial configurations, temporal constraints, or spatio-temporal dependencies is a major challenge in various application domains of current AI research. One of the research areas concerned with such topics is the field of Qualitative Spatial and Temporal Reasoning (QSTR). More precisely, research topics in QSTR are formalisms and algorithmic methods for processing qualitative i...

Commonsense reasoning, in particular qualitative spatial and temporal reasoning (QSTR), provides flexible and intuitive methods for reasoning about vague and uncertain information including spatial orientation, topology and proximity. Despite a number of theoretical advances in QSTR, there are relatively few applications that employ these methods. The central problem is a significant lack of ap...

Numerical approaches for representing and reasoning about information are ineffective when data is too imprecise or uncertain. People on the other hand cope very effectively with vague information in daily life, for example when using spatial or temporal information. This has motivated the field of qualitative spatiotemporal reasoning (QSTR), which focuses on coarse, qualitative distinctions be...

Commonsense reasoning, in particular qualitative spatial and temporal reasoning (QSTR), provides flexible and intuitive methods for reasoning about vague and uncertain information including temporal duration and ordering, and spatial orientation, topology and distance. Despite significant theoretical advances in QSTR, there is a distinct absence of applications that employ these methods. The ce...

The human pathogen Vibrio cholerae is an aquatic bacterium associated with zooplankton and their chitinous exoskeletons. On chitinous surfaces, V. cholerae initiates a developmental programme, known as natural competence, to mediate transformation, which is a mode of horizontal gene transfer. Competence facilitates the uptake of free DNA and recombination into the bacterial genome. Recent studi...

A wide variety of qualitative spatial and temporal reasoning systems have now been developed that formalise various commonsense aspects of space and time. Despite this, relatively few applications have made use of the reasoning tasks provided by these systems. We address this in a novel way by adopting the perspective of application designers. We present an outline of QSTR application theory, a...