A deductive solution for plan generation
New Generation Computing
Reasoning about knowledge
Space Complexity in Propositional Calculus
SIAM Journal on Computing
Weak, strong, and strong cyclic planning via symbolic model checking
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
Verification of Multiagent Systems via Unbounded Model Checking
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Knowing Minimum/Maximum n Formulae
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Verifying time, memory and communication bounds in systems of reasoning agents
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Verifying Resource Requirements for Distributed Rule-Based Systems
RuleML '08 Proceedings of the International Symposium on Rule Representation, Interchange and Reasoning on the Web
Verifying Time and Communication Costs of Rule-Based Reasoners
Model Checking and Artificial Intelligence
Knowing Minimum/Maximum n Formulae
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Modal logics for communicating rule-based agents
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Executable specifications of resource-bounded agents
Autonomous Agents and Multi-Agent Systems
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Memory bounds may limit the ability of a reasoner to make inferences and therefore affect the reasoner's usefulness. In this paper, we propose a framework to automatically verify the reasoning capabilities of propositional memory-bounded reasoners which have a sequential architecture. Our framework explicitly accounts for the use of memory both to store facts and to support backtracking in the course of deductions. We describe an implementation of our framework in which proof existence is recast as a strong planning problem, and present results of experiments using the MBP planner which indicate that memory bounds may not be trivial to infer even for simple problems, and that memory bounds and length of derivations are closely inter-related.