A theory of diagnosis from first principles
Artificial Intelligence
On tests for hypothetical reasoning
Readings in model-based diagnosis
Distinguishing tests for nondeterministic and probabilistic machines
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
Extending Graphplan to handle uncertainty and sensing actions
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Model-based adaptation for self-healing systems
WOSS '02 Proceedings of the first workshop on Self-healing systems
History-based diagnosis templates in the framework of the situation calculus
AI Communications - Special issue on KI-2001
Robust Agent Control of an Autonomous Robot with Many Sensors and Actuators
Robust Agent Control of an Autonomous Robot with Many Sensors and Actuators
Model-based systems in the automotive industry
AI Magazine
Monitoring the generation and execution of optimal plans
Monitoring the generation and execution of optimal plans
Integrating planning and execution in stochastic domains
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
Belief management for high-level robot programs
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Intelligent Execution Monitoring in Dynamic Environments
Fundamenta Informaticae - The 1st International Workshop on Knowledge Representation and Approximate Reasoning (KR&AR)
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Non-deterministic reality is a severe challenge for autonomous robots. Malfunctioning actions, inaccurate sensor perception and exogenous events easily lead to inconsistencies between an actual situation and the internal knowledge-base encoding a robot's belief. For a viable reasoning in dynamic environments, a robot is thus required to efficiently cope with such inconsistencies and maintain a consistent knowledge-base as fundament for its decision-making.In this paper, we present a belief management system based on the well-known agent programming language IndiGolog and history-based diagnosis. Extending the language's default mechanisms, we add a belief management system that is capable of handling several fault types that lead to belief inconsistencies. First experiments in the domain of service robots show the effectiveness of our approach.