TINA: a natural language system for spoken language applications
Computational Linguistics
Agents that reduce work and information overload
Communications of the ACM
SNePS: a logic for natural language understanding and commonsense reasoning
Natural language processing and knowledge representation
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Understanding Natural Language
Understanding Natural Language
Learning Collective Behaviour from Local Interactions
CEEMAS '01 Revised Papers from the Second International Workshop of Central and Eastern Europe on Multi-Agent Systems: From Theory to Practice in Multi-Agent Systems
Enabling technology for multilingual natural language generation: the KPML development environment
Natural Language Engineering
Unspoken rules of spoken interaction
Communications of the ACM - Human-computer etiquette
A robust system for natural spoken dialogue
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Distributing representation for robust interpretation of dialogue utterances
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
GENIO: an ambient intelligence application in home automation and entertainment environment
Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
ARTIMIS: natural dialogue meets rational agency
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
WI-IATW '07 Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
Semantic relatedness in semantic networks
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
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This paper focuses on the human-machine communication within the framework of intelligent agents. We propose a generic architecture provided with a natural language (NL) algorithm for command interpretation that can be adapted to different agent's domains. Our NL architecture only depends on the agent's code and its domain ontology. We consider two classical approaches for NL command interpretation: the top-down approach, which relies on the agent's model syntactical constraints, and the bottom-up approach which relies on the set of the agent's possible actions. We propose to combine both approaches in a bottomup based algorithm that makes use of agent's constraints. We propose a comparative evaluation of these three algorithms.