A knowledge-intensive, integrated approach to problem solving and sustained learning
A knowledge-intensive, integrated approach to problem solving and sustained learning
Explanation Patterns: Understanding Mechanical and Creatively
Explanation Patterns: Understanding Mechanical and Creatively
COMPSAC '04 Proceedings of the 28th Annual International Computer Software and Applications Conference - Volume 01
Explanation in Case-Based Reasoning---Perspectives and Goals
Artificial Intelligence Review
An evaluation of the usefulness of case-based explanation
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
Mapping goals and kinds of explanations to the knowledge containers of case-based reasoning systems
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Contextualised ambient intelligence through case-based reasoning
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
Using activity theory to model context awareness
MRC'05 Proceedings of the Second international conference on Modeling and Retrieval of Context
Explanatory Capabilities in the CREEK Knowledge-Intensive Case-Based Reasoner
Proceedings of the 2008 conference on Tenth Scandinavian Conference on Artificial Intelligence: SCAI 2008
Intelligible TinyOS sensor systems: explanations for embedded software
CONTEXT'11 Proceedings of the 7th international and interdisciplinary conference on Modeling and using context
Modelling with problem frames: explanations and context in ambient intelligent systems
CONTEXT'11 Proceedings of the 7th international and interdisciplinary conference on Modeling and using context
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Ambient intelligent systems are context aware by perceiving and reasoning about their environment, they perceive the needs of their users and proactively respond to these needs by being context sensitive. Users do not interact with these systems by traditional means only, but also through behavioural interfaces. This combination of mixed initiative systems and unconventional interfaces puts strong requirements on the explanatory capabilities of any system. The work presented here focuses on explaining the behaviour of an ambient intelligent systems to its users. It demonstrates how explanations can be combined with context to deal with the different types of explanations that are required for a meaningful interaction of a system and its users.