Organisational Intelligence and Distributed AI

The analysis of this chapter starts from organisational theory, and from this it draws conclusions for the design, and possible organisational applications, of Distributed AI systems. We first review how the concept of organisations has emerged from non-organised "blackbox" entities to so-called "computerised" organisations. Within this context organisational researchers have started to redesign their models of intelligent organisations with respect to the availability of advanced computing technology. The recently emerged concept of Organisational Intelligence integrates these efforts in that it suggests five components of intelligent organisational skills (communication, memory, learning, cognition, problem solving). The approach integrates human and computer-based information processing and problem solving capabilities.<br/

A high-level architecture for believable social agents

The creation of virtual humans capable of behaving and interacting realistically with each other requires the development of autonomous believable social agents. Standard goal-oriented approaches are not well suited to it because they don't take into account important characteristics identified by the social sciences. This paper tackles the issue of a general social reasoning mechanism, discussing its basic functional requirements using a sociological perspective, and proposing a high-level architecture based on Roles, Norms, Values and Type

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

Expressing social attitudes in virtual agents for social training games

The use of virtual agents in social coaching has increased rapidly in the last decade. In order to train the user in different situations than can occur in real life, the virtual agent should be able to express different social attitudes. In this paper, we propose a model of social attitudes that enables a virtual agent to reason on the appropriate social attitude to express during the interaction with a user given the course of the interaction, but also the emotions, mood and personality of the agent. Moreover, the model enables the virtual agent to display its social attitude through its non-verbal behaviour. The proposed model has been developed in the context of job interview simulation. The methodology used to develop such a model combined a theoretical and an empirical approach. Indeed, the model is based both on the literature in Human and Social Sciences on social attitudes but also on the analysis of an audiovisual corpus of job interviews and on post-hoc interviews with the recruiters on their expressed attitudes during the job interview

Fuzzy-Based Intelligent Sensors: Modeling, Design, Application

This paper presents a modeling of intelligent sensors based on a representation of the sensor by services it uses or it proposes, and by its USer Operating Modes (USOMs). This modeling is used for the definition of the reactive layer of distributed agent based intelligent sensors. Our area of interest is the agent-level layer in which the concept of IIC (Intelligent Instrument Cluster) is defined. An application that uses fuzzy-based intelligent sensors is presented in order to illustrate the concepts