Abstract

Abstract

Abstract
Heterogeneous agents that execute in dynamic, uncertain, partially cooperative, partially adversely environments have to take their decisions rapidly with an incomplete knowledge of actual environment conditions. This paper discusses different level of abstractions in agent's development for this type of domain, explains the principles of offline debugging and employs these principles in robotic agent's teams through the use of a new visual debugging tool. We argue that during the development of such complex agents, understanding agent reasoning is of crucial importance to the developer and that such understanding can only be done, in most of the cases, using an offline analysis of the agent's decisions. In order for the developer to rapidly perceive agent's reasoning we advocate visual debugging of the agent knowledge and reasoning at several levels of abstraction and at several different functional views. These principles have been applied with success in the context of a robotic soccer 2D simulation league team through the development of tools and extensive use of these analysis principles.

Abstract
This chapter addresses up-to-date research development regarding the adoption of more natural forms of interaction in the Serious Games for Rehabilitation domain of application. The chapter starts by presenting fundamental concepts on Serious Games illustrated by relevant applications. It describes the main problems involved and how Serious Games can benefit the process of rehabilitation. A comprehensive literature survey is presented and accompanied by a proposed set of classification criteria towards a taxonomy. From this study, a main research opportunity the authors identified is the potential benefits of the adoption of natural interaction modalities. The remainder of the chapter presents the authors' recent work on this subject, including the description and design of game prototypes using alternative and natural interaction modalities. The chapter presents experiments and the results of a user study in order to make it possible to conclude about the benefits of the newer forms of interaction. From this study, it was concluded that the introduction of the natural interaction modalities has increased the attractiveness and intuitiveness of the prototyped Serious Game. This important result is a motivating factor to improve the interaction mechanisms and conduct studies with distinct tasks and larger samples of users/patients. Lastly, the authors report identified research opportunities and open problems. © 2012, IGI Global.

Abstract
Dance movements are a complex class of human behavior which convey forms of non-verbal and subjective communication that are performed as cultural vocabularies in all human cultures. The singularity of dance forms imposes fascinating challenges to computer animation and robotics, which in turn presents outstanding opportunities to deepen our understanding about the phenomenon of dance by means of developing models, analyses and syntheses of motion patterns. In this article, we formalize a model for the analysis and representation of popular dance styles of repetitive gestures by specifying the parameters and validation procedures necessary to describe the spatiotemporal elements of the dance movement in relation to its music temporal structure (musical meter). Our representation model is able to precisely describe the structure of dance gestures according to the structure of musical meter, at different temporal resolutions, and is flexible enough to convey the variability of the spatiotemporal relation between music structure and movement in space. It results in a compact and discrete mid-level representation of the dance that can be further applied to algorithms for the generation of movements in different humanoid dancing characters. The validation of our representation model relies upon two hypotheses: (i) the impact of metric resolution and (ii) the impact of variability towards fully and naturally representing a particular dance style of repetitive gestures. We numerically and subjectively assess these hypotheses by analyzing solo dance sequences of Afro-Brazilian samba and American Charleston, captured with a MoCap (Motion Capture) system. From these analyses, we build a set of dance representations modeled with different parameters, and re-synthesize motion sequence variations of the represented dance styles. For specifically assessing the metric hypothesis, we compare the captured dance sequences with repetitive sequences of a fixed dance motion pattern, synthesized at different metric resolutions for both dance styles. In order to evaluate the hypothesis of variability, we compare the same repetitive sequences with others synthesized with variability, by generating and concatenating stochastic variations of the represented dance pattern. The observed results validate the proposition that different dance styles of repetitive gestures might require a minimum and sufficient metric resolution to be fully represented by the proposed representation model. Yet, these also suggest that additional information may be required to synthesize variability in the dance sequences while assuring the naturalness of the performance. Nevertheless, we found evidence that supports the use of the proposed dance representation for flexibly modeling and synthesizing dance sequences from different popular dance styles, with potential developments for the generation of expressive and natural movement profiles onto humanoid dancing characters.

Abstract
Several knowledge areas such as psychology, medicine and computer science have been devoting serious efforts regarding emotional state definition, identification and assessment. This project consists in an automatic emotion assessment tool based on biometric data acquisition supported by low-budget biometric devices as a electroencephalograph and a galvanic skin response. The classification is grounded on data analysis and processing of standard emotional induction methods. The numerous conducted experimental sessions, alongside with the developed support tools, allowed the extraction of conclusions such as the capability of effectively performing automatic classification of the subject's predominant emotional state. The developed tool's success rate, validated against self assessment interviews, was approximately 75%. It was also experimentally concluded that female subjects are emotionally more active and easily induced than males. © 2008 IEEE.