Modeling Ambiguity in a Multi-Agent System

This paper investigates the formal pragmatics of ambiguous expressions by modeling ambiguity in a multi-agent system. Such a framework allows us to give a more refined notion of the kind of information that is conveyed by ambiguous expressions. We analyze how ambiguity affects the knowledge of the dialog participants and, especially, what they know about each other after an ambiguous sentence has been uttered. The agents communicate with each other by means of a TELL-function, whose application is constrained by an implementation of some of Grice's maxims. The information states of the multi-agent system itself are represented as a Kripke structures and TELL is an update function on those structures. This framework enables us to distinguish between the information conveyed by ambiguous sentences vs. the information conveyed by disjunctions, and between semantic ambiguity vs. perceived ambiguity.Comment: 7 page

Mental states in communication

Abstract. This paper is concerned with the mental processes involved in intentional communication. I describe an agent's cognitive architecture as the set of cognitive dynamics (i.e., sequences of mental states with contents) she may entertain. I then describe intentional communication as one such specific dynamics, arguing against the prevailing view that communication consists in playing a role in a socially shared script. The cognitive capabilities needed for such dynamics are midreading (i.e., the ability to reason upon another individual's mental states), and communicative planning (i.e., the ability to dynamically represent and act in a communicative situation)

The Tumblarians

This paper examines the tumblarians as an information community and discusses community membership, information behaviours, and complementary models for a situated understanding of this unique personal-professional community. A review of the literature concerning LIS bloggers is presented as a complement to the tumblarians, who have no in depth treatment in the research as yet. Characteristics particular to the tumblarians are explored through informal conversation with a community member, and Fisher, Unruh, and Durrance\u27s (2003) information communities model is employed to provide a deeper understanding of the information behaviour of the tumblarians. This paper offers suggestions for future research based on the preliminary findings of the tumblarians as LIS bloggers and a virtual community

End-to-end optimization of goal-driven and visually grounded dialogue systems

End-to-end design of dialogue systems has recently become a popular research topic thanks to powerful tools such as encoder-decoder architectures for sequence-to-sequence learning. Yet, most current approaches cast human-machine dialogue management as a supervised learning problem, aiming at predicting the next utterance of a participant given the full history of the dialogue. This vision is too simplistic to render the intrinsic planning problem inherent to dialogue as well as its grounded nature, making the context of a dialogue larger than the sole history. This is why only chit-chat and question answering tasks have been addressed so far using end-to-end architectures. In this paper, we introduce a Deep Reinforcement Learning method to optimize visually grounded task-oriented dialogues, based on the policy gradient algorithm. This approach is tested on a dataset of 120k dialogues collected through Mechanical Turk and provides encouraging results at solving both the problem of generating natural dialogues and the task of discovering a specific object in a complex picture

From Monologue to Dialogue: Natural Language Generation in OVIS

This paper describes how a language generation system that was originally designed for monologue generation, has been adapted for use in the OVIS spoken dialogue system. To meet the requirement that in a dialogue, the system's utterances should make up a single, coherent dialogue turn, several modifications had to be made to the system. The paper also discusses the influence of dialogue context on information status, and its consequences for the generation of referring expressions and accentuation

Mechanisms of common ground in case-based web discussions in teacher education

Previous studies suggest that before the participants in Web-based conferencing can reach deeper level interaction and learning, they have to gain an adequate level of common ground in terms of shared mutual understanding, knowledge, beliefs, assumptions, and pre-suppositions (Clark & Schaefer, 1989; Dillenbourg, 1999). In this paper, the main purpose is to explore how participants establish and maintain common ground in order to reach deeper level interaction in case-based Web-discussions. The subjects in this study consisted of 68 pre-service teachers and 7 mentors from three universities, who participated in the Web-based conferencing course for eight weeks. The written discussion data were analyzed by means of a combination of quantitative and qualitative methods. The results suggest that in order to establish common ground it is essential that the participants, especially as fellow students, not only show evidence of their understandings through written feedback, but also provide support to their peers in their replies. Presenting questions also signals the participant’s willingness to continue the discussion, which is essential for maintaining common ground

Satirical Politics and Late-Night Television Ratings

Since the 2016 Presidential election, it has become increasingly difficult to turn on the television or log onto social media without being informed of everything happening at The White House. This includes late-night television. What once was meant for humorous jokes and celebrity interviews suitable for any pop culture follower has not gotten less funny, but nowadays, the jokes are not always jokes. Satirical news has been around for a long time with The Daily Show and The Colbert Report, but as of 2016, the line between fact and fiction cannot be as easily differentiated between as it used to. Now that late-night programs such as Jimmy Kimmel Live, The Late Show, Late Night and even Jimmy Fallon’s version of The Tonight Show have begun making political statements and producing politically motivated skits, my research is asking the question: How do people like this mix of business and pleasure, and what impact is this shift in content having on the shows’ ratings? Are people switching off their favorite late-night programs because where they once went for a break from reality became a reminder of it, instead