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Understanding the mental state of other people is an important skill for intelligent agents and robots to operate within social environments. However, the mental processes involved in 'mind-reading' are complex. One explanation of such processes is Simulation Theory — it is supported by a large body of neuropsychological research. Yet, determining the best(More)
Ontologies are a powerful means for expressing and sharing knowledge in a meaningful way, and are becoming accepted as a viable modelling approach. The purpose of this paper is to enhance the representations used by robots by incorporating ontologies and implementing reasoning services that can exploit the information inherent within ontology based(More)
Rich computer simulations or quantitative models can enable an agent to realistically predict real-world behavior with precision and performance that is difficult to emulate in logical formalisms. Unfortunately, such simulations lack the deductive flexibility of techniques such as formal logics and so do not find natural application in the deductive(More)
The ASMO Cognitive Architecture has been developed to support key capabilities: attention, awareness and self-modification. In this paper we describe the underlying attention model in ASMO. The ASMO Cognitive Architecture is inspired by a biological attention theory, and offers a mechanism for directing and creating behaviours, beliefs, anticipation,(More)
Defeasible Logic is a promising representation for legal knowledge that appears to overcome many of the deficiencies of previous approaches to representing legal knowledge. Unfortunately, an immediate application of technology to the challenges of generating theories in the legal domain is an expensive and computationally intractable problem. So, in light(More)
This paper introduces the Slick architecture and outlines how it may be applied to solve the well known Egg-Cracking Problem. In contrast to other solutions to this problem that are based on formal logics, the Slick architecture is based on general purpose and low-resolution quantitative simulations. On this benchmark problem, the Slick architecture offers(More)
Defeasible logic is a non-monotonic logic with applications in rule-based domains such as law. To ease the development and improve the accuracy of expert systems based on defeasible logic, it is desirable to automatically induce a theory of the logic from a training set of precedent data. Empirical evidence suggests that minimal theories that describe the(More)
People are accustomed to directing other people's attention using pointing gestures. People enact and interpret pointing commands often and effortlessly. If robots understand human intentions (e.g. as encoded in pointing-gestures), they can reach higher levels of engagement with people. This paper explores methods that robots can use to allow people to(More)
As social robots are designed to interact with humans in un-structured environments, they need to be aware of their surroundings, focus on significant events and ignore insignificant events in their environments. Humans have demonstrated a good example of adaptation to habituate and sensitise to significant and insignificant events respectively. Based on(More)
To perform complex tasks, a team of robots requires both reactive and deliberative planning. For reactive control, a restricted variant of Linear Temporal Logic called General Reactivity(1) can be used to synthesize correct-by-construction controllers in polynomial time, but they often ignore time and resource constraints to maintain tractable synthesis.(More)