In this paper we present some concepts and their relations that are necessary for modeling autonomous agents in an environment that is governed by some (social) norms. We divide the norms over three levels: the private level the contract level and the convention level. We show how deontic logic can be used to model the concepts and how the theory of speech acts can be used to model the generation of (some of) the norms. Finally we give some idea about (...) an agent architecture incorporating the social norms based on a BDI framework. (shrink)

We use the example of the introduction of the anti-smoking legislation to model the relationship between the cultural make-up, in terms of values, of societies and the acceptance of and compliance with norms. We present two agent-based simulations and discuss the challenge of modeling sanctions and their relation to values and culture.

Aim of the present paper is to provide a formal characterization of various different notions of responsibility within groups of agents (Who did that? Who gets the blame? Who is accountable for that? etc.). To pursue this aim, the papers proposes an organic analysis of organized collective agency by tackling the issues of organizational structure, role enactment, organizational activities, task-division and task-allocation. The result consists in a semantic framework based on dynamic logic in which all these concepts can be represented (...) and in which various notions of responsibility find a formalization. The background motivation of the work consists in those responsibility-related issues which are of particular interest for the theory and development of multi-agent systems. (shrink)

One way to allocate tasks to agents is by ascribing them obligations. From obligations to be, agents are able to infer what are the forbidden, permitted and obligatory actions they may perform, by using the well-known Meyer’s reduction from obligations to be to obligations to do. However, we show through an example that this method is not completely adequate to guide agents’ decisions. We then propose a solution using, instead of obligations, the concept of ‘responsibility’. To formalise responsibility we use (...) a multiagent extension of propositional dynamic logic as framework, and then we define some basic concepts, such as ‘agent ability’, also briefly discussing the problem of uniform strategies and a possible solution. In the last part, we show that our framework can be used in the specification of normative multiagent systems, by presenting an extensive running example. (shrink)

The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the “phase 2” of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by the app are all sent to a nation-wide server, raises concerns about citizens’ privacy (...) and needlessly strong digital surveillance, thus alerting us to the need to minimize personal data collection and avoiding location tracking. We advocate the conceptual advantage of a decentralized approach, where both contact and location data are collected exclusively in individual citizens’ “personal data stores”, to be shared separately and selectively, voluntarily, only when the citizen has tested positive for COVID-19, and with a privacy preserving level of granularity. This approach better protects the personal sphere of citizens and affords multiple benefits: it allows for detailed information gathering for infected people in a privacy-preserving fashion; and, in turn this enables both contact tracing, and, the early detection of outbreak hotspots on more finely-granulated geographic scale. The decentralized approach is also scalable to large populations, in that only the data of positive patients need be handled at a central level. Our recommendation is two-fold. First to extend existing decentralized architectures with a light touch, in order to manage the collection of location data locally on the device, and allow the user to share spatio-temporal aggregates—if and when they want and for specific aims—with health authorities, for instance. Second, we favour a longer-term pursuit of realizing a Personal Data Store vision, giving users the opportunity to contribute to collective good in the measure they want, enhancing self-awareness, and cultivating collective efforts for rebuilding society. (shrink)

In order to design and implement electronic institutions that incorporate norms governing the behavior of the participants of those institutions, some crucial steps should be taken. The first problem is that human norms are (on purpose) specified on an abstract level. This ensures applicability of the norms over long periods of time in many different circumstances. However, for an electronic institution to function according to those norms, they should be concrete enough to be able to check them run time. A (...) second problem is that norms describe which behavior is desirable and permitted, but not how this is achieved in an institution. In the “real world" regulations often indicate procedures for implementing and enforcing the law. Likewise we should devise means to annotate the norms with practical aspects such as enforcement mechanisms, sanctions, etc. in order to get requirements for an institution that will enforce norms (by either constraining behavior within the norms or reacting to violation of the norms). The choice of which kind of mechanism is chosen is not a normative one, but usually based on criteria of efficiency and/or feasibility of the mechanism. In this paper we present our view on how to approach these problems and other related issues to be solved in order to develop e-institutions capable to operate in complex, highly regulated scenarios. (shrink)

During the COVID-19 crisis there have been many difficult decisions governments and other decision makers had to make. E.g. do we go for a total lock down or keep schools open? How many people and which people should be tested? Although there are many good models from e.g. epidemiologists on the spread of the virus under certain conditions, these models do not directly translate into the interventions that can be taken by government. Neither can these models contribute to understand the (...) economic and/or social consequences of the interventions. However, effective and sustainable solutions need to take into account this combination of factors. In this paper, we propose an agent-based social simulation tool, ASSOCC, that supports decision makers understand possible consequences of policy interventions, but exploring the combined social, health and economic consequences of these interventions. (shrink)