Papers about Agent's Processing

The paper presents a novel sentence-based language classifier that accepts a sentence as input and produces a confidence value for each target language. The proposed classifier incorporates Unicode based features and a neural network. The three features Unicode, exclusive Unicode and word matching score are extracted and fed to a neural network for obtaining a final confidence value. The word matching score is calculated by matching words in an input sentence against a common word... Read more

A great challenge that is to be faced in the design of virtual agents is the issue of credibility, not only in the agent's aspect but also in its behavior. To be believable, the agent has to decide what to do next according to the internal and external variables of the agent. Besides others, we have to deal with the problem of action selection which can be resumed to choose the most appropriate action among... Read more

This paper aims to present e the work developed at Cnotinfor within the LIREC project. We will present Little Mozart mind architecture and facial expressions. Our goal is to create a virtual e-learning agent capable of establishing meaningful interactions with children on how to compose and improve their knowledge of melodic composition and basics of musical language. In order to make our agent believable and engaging we resorted to facial and body 3D modeling techniques... Read more

Emotive virtual humans (VHs) are important for affective interactions with embodied conversation agents. However, emotive VHs require significant resources and time. As an example, the VHs in movies and video games require teams of animators and months of work. VHs can also be imbued with emotion using appraisal theory methods that use psychology based models to generate emotions by using the VH's goals and beliefs to evaluate external events. These external events require manual tagging... Read more

Several challenges remain in the effort to build software capable of conducting realtime dialogue with people. Part of the problem has been a lack of realtime flexibility, especially with regards to turntaking. We have built a system that can adapt its turntaking behavior in natural dialogue, learning to minimize unwanted interruptions and "awkward silences". The system learns this dynamically during the interaction in less than 30 turns, without special training sessions. Here we describe the... Read more

Enabling virtual agents to quickly and accurately infer users' psychological characteristics such as their personality could support a broad range of applications in education, training, and entertainment. With a focus on narrative-centered learning environments, this paper presents an inductive framework for inferring users' psychological characteristics from observations of their interactions with virtual agents. Trained on traces of users' interactions with virtual agents in the environment, psychological user models are induced from the interactions to accurately... Read more

Computational modeling of emotion, physiology and personality is a major challenge in order to design believable virtual humans. These factors have an impact on both the individual behavior and the collective one. This requires to take into account the empathy phenomenon. Furthermore, in a crisis simulation context where the virtual humans can be contaminated by radiological or chemical substances, empathy may lead to placebo or nocebo effects. Stemming from works in the multi-agent systems domain, our... Read more

Avatars are frequently used in virtual worlds and online games to convey emotions across cultures. However, our previous study suggested there are cultural differences in recognizing avatar's facial expressions [1]. Yuki et al.'s study using emoticons and photorealistic human face images suggests Americans tend to interpret emotions based on the mouth, while Japanese tend to focus on the eyes [2]. Inspired by Yuki's study, this study uses cartoonish avatar faces to find cultural differences in... Read more

We present recent extensions for the intelligent virtual agent development platform Pogamut 3. These extensions are: the agent coordination language StorySpeak designed for the purposes of storytelling applications, support for gestures based on BML, the visual editor of reactive plans, connection of the cognitive architecture ACT-R, an educational application aimed at orientation in urban areas and finally an emotional model. Read more

Memory is a vital capability for intelligent social Companions. In this paper, we introduce a simple memory model that allows a Companion to maintain a long-term relationship with the user by remembering past experiences in order to personalise interaction. Additionally, we implemented a situational forgetting mechanism that gives the Companion the ability to protect the user's privacy by not disclosing sensitive data. Two test scenarios are used to demonstrate these abilities in our Companions. Read more