Soft systems methodology in action
Soft systems methodology in action
Conversational Case-Based Reasoning
Applied Intelligence
Interactive Case-Based Reasoning in Sequential Diagnosis
Applied Intelligence
Activating CBR Systems Through Autonomous Information Gathering
ICCBR '99 Proceedings of the Third International Conference on Case-Based Reasoning and Development
Conversational Case-Based Planning for Agent Team Coordination
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Advances in conversational case-based reasoning
The Knowledge Engineering Review
Autonomic self healing and recovery informed by environment knowledge
Artificial Intelligence Review
Increasing dialogue efficiency in case-based reasoning without loss of solution quality
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Evaluating CBR systems using different data sources: a case study
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
Case-based reasoning for autonomous service failure diagnosis and remediation in software systems
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
Conversational Case-Based Reasoning in Medical Classification and Diagnosis
AIME '09 Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine
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Self-healing and recovery informed by environment knowledge (SHRIEK) is an autonomic computing approach to improving the robustness of computing systems. Case-based reasoning (CBR) is used to guide fault diagnosis and enable learning from experience, and rule-based reasoning to enable fault remediation and recovery informed by environment knowledge. Focusing on the role of conversational CBR (CCBR) in the management of faults that rely on user interaction for their detection and diagnosis, we present a hypothesis-driven approach to question selection in CCBR that aims to increase the transparency of CCBR dialogues by enabling the system to explain the relevance of any question the user is asked. We also present empirical results which suggest that there is no loss of problem-solving efficiency in the approach. Finally, we investigate the effects of the environment awareness provided by autonomous information gathering in SHRIEK on the efficiency of CCBR dialogues.