This article introduces the research issues related to and definition of normative multiagent systems. It also describes the papers selected from NorMAS05 that are part of this double special issue and relates the papers to each other. Keywords Norms . Multiagent systems . Normative multiagent systemsNormative multiagent systems as a research area can be defined as the intersection of normative systems and multiagent systems. Since the use of norms is a key element of human social intelligence, norms may be essential too for artificial agents that collaborate with humans, or that are to display behavior comparable to human intelligent behavior. By integrating norms and individual intelligence normative multiagent systems provide a promising model for human and artificial agent cooperation and co-ordination, group decision making, multiagent organizations, regulated societies, electronic institutions, secure multiagent systems, and so on.With 'normative' we mean 'conforming to or based on norms', as in normative behavior or normative judgments. According to the Merriam-Webster Online (2005) Dictionary, other meanings of normative not considered here are 'of, relating to, or determining norms or standards', as in normative tests, or 'prescribing norms', as in normative rules of ethics or normative grammar. With 'norm' we mean 'a principle

The COVID-pandemic is causing a dramatic loss of lives worldwide, challenging the sustainability of our health care systems, threatening economic meltdown, and putting pressure on the mental health of individuals (due to social distancing and lock-down measures). The pandemic is also posing severe challenges to the scientific community, with scholars under pressure to respond to policymakers' demands for advice despite the absence of adequate, trusted data. Understanding the pandemic requires fine-grained data representing specific local conditions and the social reactions of individuals. While experts have built simulation models to estimate disease trajectories that may be enough to guide decision-makers to formulate policy measures to limit the epidemic, they do not cover the full behavioural and social complexity of societies under pandemic crisis. Modelling that has such a large potential impact upon people's lives is a great responsibility. This paper calls on the scientific community to improve the transparency, access, and rigour of their models. It also calls on stakeholders to improve the rapidity with which data from trusted sources are released to the community (in a fully responsible manner). Responding to the pandemic is a stress test of our collaborative capacity and the social/economic value of research.

This special issue contains four selected and revised papers from the second international workshop on normative multiagent systems, for short NorMAS07 (Boella et al. In this editorial we discuss the shift, examples, and 10 new challenges in this more dynamic setting, which we use to introduce the papers of this special issue.Keywords Norms · Multiagent Systems · Normative multiagent systems · Social mechanism design · Artifical social systems Towards a more dynamic interactionist viewTraditionally normative systems have been studied in philosophy, sociology, law, and ethics, and during the past two decades they have been studied in deontic logic in computer science ( EON). Normative multiagent systems is a research area where the traditional normative systems and EON research fields meet agent research. The proposed solutions to the EON research problems are changing, and solutions based on multiagent systems are increasing. Gradually the EON research focus changes from logical relations among norms, to, for