Visual dialog is a task of answering a series of inter-dependent questions given an input image, and often requires to resolve visual references among the questions. This problem is different from visual question answering (VQA), which relies on spatial attention (a.k.a. visual grounding) estimated from an image and question pair. We propose a novel attention mechanism that exploits visual atte...

A modal logic is any logic for handling modalities: concepts like possibility, necessity, and knowledge. Artificial intelligence uses modal logics most heavily to represent and reason about knowledge of agents about others’ knowledge. This type of reasoning occurs in dialog, collaboration, and competition. In many applications it is also important to be able to reason about the probability of b...

To demonstrate the use of Prolog and how programming in Prolog is easy and efficient, this paper describe an implementation of the game booby-trap, a game similar to Minesweeper found on most personal computers with windows. Introduction Prolog (Programming in Logic) is a well known programming language in the field of Artificial Intelligence (AI). Although Prolog has much in common with Lisp (...

In this work we propose an interpretation of the LSA framework which leads to a data-driven “conceptual” space creation suitable for an “intuitive” conversational agent. The proposed approach allows overcoming the limitations of traditional, rule-based, chat-bots, leading to a more natural dialogue.

A system f o r computer a s s i s t e d m e d i c a l d i a g n o s i s has been developed, which i n c o r p o r a t e s an i n n o v a t i v e model o f d i a g n o s t i c l o g i c . A s u p p o r t i n g m e d i c a l d a t a base has a l s o been assembled, now c o m p r i s i n g a p p r o x i m a t e l y f i f t y p e r c e n t o f t h e major diseases o f i n t e r n a l m e d i c i n ...

This paper presents a series of measurements of the accuracy of speech understanding when grammar-based or robust approaches are used. The robust approaches considered here are based on statistical language models (SLMs) with the interpretation being carried out by phrasespotting or robust parsing methods. We propose a simple process to leverage existing grammars and logged utterances to upgrad...

In this paper we develop a semantics of our approach based on commitments and arguments for conversational agents. We propose a logical model based on CTL* (Extended Computation Tree Logic) and on dynamic logic. Called Commitment and Argument Network (CAN), our formal framework based on this hybrid approach uses three basic elements: social commitments, actions that agents apply to these commit...

This talk explores meaningfulness as an explicit design goal for conversational agents, programs that can understand and contribute to spoken dialogue with a human user in ordinary natural language. When we talk with other people, our judgments of meaning provide a systematic perspective on what we are doing. As our conversations unfold, we rely on these judgments to get our ideas across flexib...

We describe a domain-independent semantic interpretation architecture suitable for spoken dialogue systems, which uses a decision-list method to effect a transparent combination of rule-based and data-driven approaches. The architecture has been implemented and evaluated in the context of a mediumvocabulary command and control task.

Introduction We describe how spoken dialogue interfaces make a simulation-based trainer and an intelligent tutoring system into a powerful package for Naval damage control education. An advanced simulator gives a student real-time experience that would otherwise be extremely costly to provide. The dialogue interface to the simulator uses a simple finite-state script to allow the user to issue o...