Social Intelligence Design for Mediated Communication

Without abstract

Social Intelligence Design in Ambient Intelligence

This Special Issue of AI and Society contains a selection of papers presented at the 6th Social Intelligence Design Workshop held at ITC-irst, Povo (Trento, Italy) in July 2007. Being the 6th in a series means that there now is a well-established and also a growing research area. The interest in this research area is growing because, among other things, current computing technology allows other than the traditional efficiency-oriented applications associated with computer science and interface technology. For example, in Ambient Intelligence (AmI) applications we look at sensor-equipped environments and devices (robots, smart furniture, virtual humans and pets) that support their human inhabitants during their everyday activities. These everyday activities also include computer-mediated communication, collaboration and community activities

PSX : A Program that Explores Phase Portraits of Two-dimensional Piecewise Linear Differential Equations

A set of all solution curves in the phase space for ordinary differential equations is called the phase portrait. Phase portraits provide global qualitative information about how dynamical systems behave under different initial conditions. In this paper, we present a program called PSX that automatically analyzes topological structure of phase portraits for two dimensional piecewise linear differential equations. PSX has several novel features that have not been achieved before : (a) PSX possesses procedures for recognizing instances of abstract concepts defined in dynamical systems theory. PSX does not only build a memory structure for instances of abstract concepts but it also directs the search process and constructively proves that what it has found is in fact an instance of the concept. (b) Though limited to two-dimensional phase spaces, PSX is applicable to complex flows in Non-Euclidean phase spaces as well as those in Euclidean phase spaces. (c) The architecture of PSX enables qualitative analysis and quantitative analysis to interact in a cooperative manner. Qualitative analysis guides the overall analysis process. When it gets stuck due to ambiguity, qualitative analysis submits a question to the quantitative analysis and the quantitative analysis provides an answer. PSX has been implemented using Common Lisp and tested against several examples

AnimGAN: A Spatiotemporally-Conditioned Generative Adversarial Network for Character Animation

Producing realistic character animations is one of the essential tasks in human-AI interactions. Considered as a sequence of poses of a humanoid, the task can be considered as a sequence generation problem with spatiotemporal smoothness and realism constraints. Additionally, we wish to control the behavior of AI agents by giving them what to do and, more specifically, how to do it. We proposed a spatiotemporally-conditioned GAN that generates a sequence that is similar to a given sequence in terms of semantics and spatiotemporal dynamics. Using LSTM-based generator and graph ConvNet discriminator, this system is trained end-to-end on a large gathered dataset of gestures, expressions, and actions. Experiments showed that compared to traditional conditional GAN, our method creates plausible, realistic, and semantically relevant humanoid animation sequences that match user expectations.Comment: Submitted to ICIP 202

Structural Analysis of Instruction Utterances

Abstract. In realizing video retrieval system, the crucial point is how to provide an effective access method of video contents. This paper fo-cuses on Japanese cooking instruction utterances and describes a method of analyzing structure of them, which leads to a summary of video. We detect a hierarchical structure of video contents by using linguistic and visual information. We found that the integration of visual information can improve the detection of task units better than using linguistic in-formation alone.