Abstract In 1997, Robert Axelrod wondered in a highly influential paper" If people tend to
become more alike in their beliefs, attitudes, and behavior when they interact, why do not all …

Over the last few years there has been rapid research growth into eXplainable Artificial
Intelligence (XAI) and the closely aligned Interpretable Machine Learning (IML). Drivers for …

Agents and Multiagent Systems: Themes, Approaches, and Challenges Page 1 Agents and
Multiagent Systems: Themes, Approaches, and Challenges Michael N. Huhns* Dept of …

¿ De qué manera las situaciones sociales influyen en el uso del lenguaje y en el discurso?
Este libro constituye la primera monografía en presentar una teoría multidisciplinaria del …

Norms and normative multiagent systems have become the subjects of interest for many
researchers. Such interest is caused by the need for agents to exploit the norms in …

Concepts based on full-blown collective intentionality (aboutness), viz., we-mode
intentionality, are central for understanding and explaining the social world. The book …

Scenario analysis has evolved notably in its 50-year history and today there is a large
diversity in the scenarios that are developed. Establishing an overview of this diversity would …

When designing an agent-based simulation, an important question to answer is how to
model the decision making processes of the agents in the system. A large number of agent …

Social Signal Processing is the research domain aimed at bridging the social intelligence
gap between humans and machines. This paper is the first survey of the domain that jointly …

In the new AI of the 90s an important stream is artificial social intelligence. In this work basic
ontological categories for social action, structure, and mind are introduced. Sociality (social …