Training an adaptive dialogue policy for interactive learning of visually grounded word meanings

We present a multi-modal dialogue system for interactive learning of perceptually grounded word meanings from a human tutor. The system integrates an incremental, semantic parsing/generation framework - Dynamic Syntax and Type Theory with Records (DS-TTR) - with a set of visual classifiers that are learned throughout the interaction and which ground the meaning representations that it produces. We use this system in interaction with a simulated human tutor to study the effects of different dialogue policies and capabilities on the accuracy of learned meanings, learning rates, and efforts/costs to the tutor. We show that the overall performance of the learning agent is affected by (1) who takes initiative in the dialogues; (2) the ability to express/use their confidence level about visual attributes; and (3) the ability to process elliptical and incrementally constructed dialogue turns. Ultimately, we train an adaptive dialogue policy which optimises the trade-off between classifier accuracy and tutoring costs.Comment: 11 pages, SIGDIAL 2016 Conferenc

Learning policy constraints through dialogue

Publisher PD

"How May I Help You?": Modeling Twitter Customer Service Conversations Using Fine-Grained Dialogue Acts

Given the increasing popularity of customer service dialogue on Twitter, analysis of conversation data is essential to understand trends in customer and agent behavior for the purpose of automating customer service interactions. In this work, we develop a novel taxonomy of fine-grained "dialogue acts" frequently observed in customer service, showcasing acts that are more suited to the domain than the more generic existing taxonomies. Using a sequential SVM-HMM model, we model conversation flow, predicting the dialogue act of a given turn in real-time. We characterize differences between customer and agent behavior in Twitter customer service conversations, and investigate the effect of testing our system on different customer service industries. Finally, we use a data-driven approach to predict important conversation outcomes: customer satisfaction, customer frustration, and overall problem resolution. We show that the type and location of certain dialogue acts in a conversation have a significant effect on the probability of desirable and undesirable outcomes, and present actionable rules based on our findings. The patterns and rules we derive can be used as guidelines for outcome-driven automated customer service platforms.Comment: 13 pages, 6 figures, IUI 201

Negotiating with a logical-linguistic protocol in a dialogical framework

This book is the result of years of reflection. Some time ago, while working in commodities, the author felt how difficult it was to decide the order in which to use arguments during a negotiation process. What would happen if we translated the arguments into cards and played them according to the rules of the Bridge game? The results were impressive. There was potential for improvement in the negotiation process. The investigation went deeper, exploring players, cards, deals and the information concealed in the players´ announcements, in the cards and in the deals. This new angle brought the research to NeuroLinguistic Patterns and cryptic languages, such as Russian Cards. In the following pages, the author shares her discovery of a new application for Logical Dialogues: Negotiations, tackled from basic linguistic structures placed under a dialogue form as a cognitive system which ‘understands’ natural language, with the aim to solve conflicts and even to serve peace

Argumentation schemes for collaborative planning

Postprin

Properties for a formal model of collaborative dialogue

We propose a basic set of desirable properties for an abstract model of collaborative dialogue among agents. The abstraction comprehends the underlying logic of the agents, as well as the interaction protocol. The properties pursue the characterization of finite dialogues, with reasonable conclusions (based on what the participants have said), in which everything said is relevant and everything relevant is said. To this end, two levels of relevance (direct and potential ) are defined, based on the notions of inference and abduction, respectively. Illustrative examples, using mainly the DeLP formalism, are provided.Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Arguing and negotiating in the presence of social influences

Postprin

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications