Temporal ontology and temporal reference
Computational Linguistics - Special issue on tense and aspect
Intention is choice with commitment
Artificial Intelligence
Artificial Intelligence - Special volume on natural language processing
Probabilistic Horn abduction and Bayesian networks
Artificial Intelligence
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Coupling CCG and hybrid logic dependency semantics
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Continual planning and acting in dynamic multiagent environments
Autonomous Agents and Multi-Agent Systems
Probabilistic semantics for cost based abduction
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
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In this paper we present a continual context-sensitive abductive framework for understanding situated spoken natural dialogue. The framework builds up and refines a set of partial defeasible explanations of the spoken input, trying to infer the speaker's intention. These partial explanations are conditioned on the eventual verification of the knowledge gaps they contain. This verification is done by executing test actions, thereby going beyond the initial context. The approach is illustrated by an example set in the context of human-robot interaction.