Supporting flexible regulation of crisis management by means of situated artificial institution

Brito, Maiquel de; Thévin, Lauren; Garbay, Catherine; Boissier, Olivier; Hübner, Jomi Fred

doi:10.1631/fitee.1500369

Cited by 6 publications

(9 citation statements)

References 17 publications

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“…Viana et al [28] created a model language to support the systematic design of adaptive normative multi-agent systems. Brito et al [29] situated norms in a hybrid, interactive, normative multi-agent system to provide a context-aware crisis regulation. Bulling et al [30] proposed a concrete executable specification language to study and analyze the effect of norms and sanctions on the behavior of rational agents.…”

Section: Modeling Social Normsmentioning

confidence: 99%

NorMASS: A normative MAS-based modeling approach for simulating incentive mechanisms of Q&A communities

et al. 2023

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Incentive mechanisms steer users in Q&A communities to achieve community goals, which need to be cautiously reviewed and revised before actual industrial application. Simulating incentive mechanisms is significant for predicting how changes in incentive mechanisms will affect community emergence, such as user answering patterns. However, due to the complexity of Q&A communities, the challenge faced by simulating incentive mechanisms lies in the difficulty of establishing micro-macro connections in the communities to simulate their emergence. To fill this gap, this paper proposes a Normative Multi-Agent System based Simulation (NorMASS) approach to simulate community emergence. The NorMASS models a Q&A community as a normative multi-agent system and adopts agents to formally express community users. Moreover, the approach provides an open-source simulator with a data generator to simulate community emergence. An evaluation of the NorMASS comparing simulation emergence with the counterpart of an actual community demonstrates that the proposed approach provides an effective solution for simulating incentive mechanisms of Q&A communities, with a similarity of 80% or above.

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Section: Modeling Social Normsmentioning

confidence: 99%

NorMASS: A normative MAS-based modeling approach for simulating incentive mechanisms of Q&A communities

et al. 2023

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“…The main idea of using artificial institutions as a counterpart of human institutions in computer systems has inspired work in MAS. In different ways, these works use the count-as relationship, established through the constitutive rules proposed by Searle, to support the regulation of the system [5]. This work considers that the constitutive relation, as well as the related concepts (e.g., statusfunctions) provide functions to be exploited by the agents to achieve their goals The purpose of this section is to review state of the art on artificial institutions with respect of the explicit representation of the functions associated to the institutional concepts.…”

Section: Institutions In Masmentioning

confidence: 99%

Coupling purposes with status-functions in artificial institutions

Cunha,

Hübner,

de Brito

2021

Preprint

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In multi-agent systems, the agents may have goals that depend on a social, shared interpretation about the facts occurring in the system. These are the so-called social goals. Artificial institutions provide such a social interpretation by assigning statuses to the concrete elements that compose the system. These statuses are supposed to enable the assignee element to perform functions that are not exclusively inherent to their design features. However, the enabled functions are not explicit in the existing models of artificial institutions. As a consequence, (i) agents may have difficulties to reasoning about how to achieve their own social goals with the help of artificial institutions and (ii) these institutions are not well instrumented to receive incoming agents, in the case of open systems. Considering those problems, this paper proposes a model to express the functions -or the purposes -associated with the status-functions helping the agents to reason about their social goals and the institution. We evaluate the model by using it in some scenarios, showing how the agents can use purposes to reason about the satisfaction of their social goals in institutional contexts and how the institution can be flexible enough to support new agents operating in the system.

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“…Theoretical aspects of the presented work were illustrated in this paper through examples from an application on crisis management. In these examples, SAI is proven to be useful to solve some issues [27][28][29][30][31]. As SAI is a general purpose model, applying it to other scenarios that can be modelled as open MAS, such as those pointed in Sect.…”

Section: Limitations and Future Workmentioning

confidence: 99%

Situated artificial institutions: stability, consistency, and flexibility in the regulation of agent societies

Brito

Hübner

Boissier

2017

Auton Agent Multi-Agent Syst

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International audienceIn multi-agent systems, norms are a usual way to regulate the behaviour of autonomous agents. To be stable in different circumstances, norms are specified using high level terms, abstracting from the particular dynamics of the environment where the agents are situated. However, applying these norms requires a proper link with a concrete environment. Detaching that link from the norms themselves provides stability to the normative regulation but raises consistency and flexibility issues. Consistency is achieved when the abstract norms are coherent with the environment under regulation. Flexibility is achieved when different kinds of norms share the same interpretation about the environmental state. These properties are provided in some current works. However, since they are interrelated, there is not, to our knowledge, a single proposal providing all of them. This paper proposes the situated artificial institution (SAI) model to address these three issues—stability, consistency, and flexibility—by conceiving norms as part of institutions that provide, through the process of constitution, a social interpretation of the environmental state. After the presentation of the formalised model of SAI, a case study is used to illustrate and test this approach

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Supporting flexible regulation of crisis management by means of situated artificial institution

Cited by 6 publications

References 17 publications

NorMASS: A normative MAS-based modeling approach for simulating incentive mechanisms of Q&A communities

NorMASS: A normative MAS-based modeling approach for simulating incentive mechanisms of Q&A communities

Coupling purposes with status-functions in artificial institutions

Situated artificial institutions: stability, consistency, and flexibility in the regulation of agent societies

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