Artificial Intelligence
An autonomous spacecraft agent prototype
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Putting the Problem Solver Back in the Driver's Seat: Contextual Control of the AMTS
ECAI '90 Workshop on Truth Maintenance Systems
A model-based approach to reactive self-configuring systems
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Scaling up logic-based truth maintenance systems via fact garbage collection
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Polarity guided tractable reasoning
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
An Autonomous Spacecraft Agent Prototype
Autonomous Robots - Special issue on autonomous agents
An Information-Theoretic Characterization of Abstraction in Diagnosis and Hypothesis Selection
Proceedings of the 5th International Symposium on Abstraction, Reformulation and Approximation
Conflict-directed A* and its role in model-based embedded systems
Discrete Applied Mathematics
Robotics and Autonomous Systems
Incremental state based diagnosis
Advanced Engineering Informatics
Set-theoretic estimation of hybrid system configurations
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Incrementally maintaining materializations of ontologies stored in logic databases
Journal on Data Semantics II
A model-based executive for commanding robot teams
ProMAS'05 Proceedings of the Third international conference on Programming Multi-Agent Systems
The route to success: a performance comparison of diagnosis algorithms
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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The trend to increasingly capable and affordable control processors has generated an explosion of embedded real-time gadgets that serve almost every function imaginable. The daunting task of programming these gadgets is greatly alleviated with real-time deductive engines that perform all execution and monitoring functions from a single core model. Fast response times are achieved using an incremental propositional deductive database (an LTMS). Ideally the cost of an LTMS's incremental update should be linear in the number of labels that change between successive contexts. Unfortunately an LTMS can expend a significant percentage of its time working on labels that remain constant between contexts. This is caused by the LTMS's conservative approach: a context switch first removes all consequences of deleted clauses, whether or not those consequences hold in the new context. This paper presents a more aggressive incremental TMS, called the ITMS, that avoids processing a significant number of these consequences that are unchanged. Our empirical evaluation for spacecraft control shows that the overhead of processing unchanged consequences can be reduced by a factor of seven.