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Dynamic and Epistemic Semantics of Questions : The Logic of Consultation

Preface This thesis is the result of my research project on the dynamic and epistemic semantics of questions, performed at the Institute for Logic, Language and Computation, University of Amsterdam, from May, 1st – July, 31st, 2000. The thesis combines aspects of semantics and artificial intelligence. Formal semantics of natural language (henceforth semantics) is, one might argue, strictly not a domain of artificial intelligence. Still, the two disciplines are closely related. In order to illustrate this, I will discuss three connections. First of all, in computational linguistics, which is usually considered a subdomain of artificial intelligence, semantic theories play a large part. Natural language processing (NLP), such as in question answering systems, information retrieval, machine translation, automatic summarisation and automated dialogue systems, depend on understanding of natural language. Therefore, semantics can provide useful insights. This thesis focusses on the semantics of questions. For NLP applications such as the ones mentioned above, the semantics of questions can play an important role. For question answering systems and information retrieval this is quite clear. These applications are directly related to the task of answering questions. To be able to give an appropriate answer to a question, one has to know what counts as an answer. Answerhood conditions is precisely what the semantics of questions is all about. Researchers who have come to the conclusion that formal theories of meaning can be useful when building NLP applications, include Scha (1983), Sadek (1999), Blackburn et al. (1999) and Hulstijn (2000). Secondly, in artificial intelligence much attention has been directed to the notions of ra-tionality and goals and intentions. In this thesis , I build on such theories in order to model the underlying goals of the participants of a consultation. Third, while (dynamic) semantics is directed towards building formal models of communication and information exchange, in the AI research field of Multi Agent Systems, attention has been directed towards building formal models of negotiation. These two are closely related. In this thesis I will bring the two even closer, as I take a model of information exchange, and add goals of the participants to the model. The language game that I will formalise is that of consultation. In consultation, two agents together deliberate on which action to take. Now, one feature of consultation is that cooperativity might be assumed: the participants help each other where possible. Also, they have a common goal: to fulfill the …