agents, in a multi agent system, communicate with each other through the process of exchanging messages which is called dialogue. multi agent organization is generally used to optimize agents’ communications. holonic organization demonstrates a self-similar recursive and hierarchical structure in which each holon may include some other holons. in a holonic system, lateral communication occurs b...

Agents, in a multi agent system, communicate with each other through the process of exchanging messages which is called dialogue. Multi agent organization is generally used to optimize agents’ communications. Holonic organization demonstrates a self-similar recursive and hierarchical structure in which each holon may include some other holons. In a holonic system, lateral communication occurs b...

This paper presents the results of the user evaluation of spoken decision support dialogue systems, which help users select from a set of alternatives. Thus far, we have modeled this decision support dialogue as a partially observable Markov decision process (POMDP), and optimized its dialogue strategy to maximize the value of the user’s decision. In this paper, we present a comparative evaluat...

We highlight the importance of dialogue management in systems that support mixed-initiative interaction. For concreteness, we focus on interaction with recommender systems. We propose an approach that uses both a dialogue grammar and a recommendation strategy. The dialogue grammar makes explicit the opportunities the user and system have for seizing and ceding the initiative. But it maintains o...

This paper describes MIMIC, an adaptive mixed initiative spoken dialogue system that provides movie showtime information. MIMIC improves upon previous dialogue systems in two respects. First, it employs initiative-oriented strategy adaptation to automatically adapt response generation strategies based on the cumulative effect of information dynamically extracted from user utterances during the ...

This paper presents and evaluates a behavior-based approach to dialogue management, where a system’s complete dialogue strategy is viewed as the result of running several dialogue behaviors in parallel leading to an emergent coherent and flexible dialogue behavior. The conducted overhearer evaluation of the behaviorbased conversational recommender system CORESONG indicates that the approach can...

In a human-computer dialogue system, the dialogue strategy can range from very restrictive to highly flexible. Each specific dialogue style has its pros and cons and a dialogue system needs to select the most appropriate style for a given user. During the course of interaction, the dialogue style can change based on a user’s response and the system observation of the user. This allows a dialogu...

Speech understanding errors in spoken dialogue systems can be frustrating for users and difficult to recover from in a mixed-initiative spoken dialogue system. Handling such errors requires both detecting error conditions and adjusting the response generation strategy accordingly. In this paper, we show that different response wording choices tend to be associated with different user behaviors ...

This paper describes a novel method by which a spoken dialogue system can learn to choose an optimal dialogue strategy from its experience interacting with human users. The method is based on a combination of reinforcement learning and performance modeling of spoken dialogue systems. The reinforcement learning component applies Q-learning (Watkins, 1989), while the performance modeling componen...