Normative Multi-agent Systems Research Articles

Exploring the Generality of Norms in Multi-Agent Systems

Norms are useful tools to regulate autonomous agents, and their generality is the focus of this paper. The generality of norms refers to the extent of behaviors the norms are capable of regulating. While very specific norms tend to be inefficient to avoid undesirable behaviors (since they are rarely activated), very general norms tend to limit excessively the options of the agents (since they are activated too often) hindering them to achieve the system goal. Therefore, a norm that efficiently regulates the agents should have a balanced generality, being neither too specific nor too general. Therefore, we consider that exploring the generality of norms is a fundamental key to obtaining efficient norms. However, the evaluation of their generality usually considers every behavior they regulate. Since it is likely an unfeasible task, in this paper, we investigate alternatives to estimate the norms generality from their syntactic characteristics. Based on these characteristics, we obtain different sequences of norms that vary, approximately, from the most specific to the most general. We assume thus that norms with a balanced generality are more easily found considering these orderings. Therefore, it is relevant to understand the impact of the syntactical characteristics in ordering the norms. In this context, we found out how different alternatives organize the norms space. This result is particularly useful for the development of algorithms for searching efficient norms that, through different strategies, may exploit how norms space is arranged and may be pruned.

Operational profile development methodology for normative multi-agent systems

Software reliability refers to the ability of a system to perform its intended function under specified conditions for a specified period of time. The first critical step in the software reliability testing process is to create a Software Operational Profile (SOP). Several methodologies for creating SOP have been proposed. Nonetheless, nearly all the proposed studies have neglected the uniqueness of the new software paradigms, despite the fact that these are generally distinguished by their own concepts and methodologies. One of these software paradigms is multi-agent systems. Rather than using a generic one, it would be more useful to propose a specific methodology for creating SOP. In this paper, we propose a methodology for developing Operational Profile for specific kinds of multi-agent systems (so-called normative multi-agent systems). A detailed case study is used to demonstrate this methodology.

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

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.

Data-Driven Revision of Conditional Norms in Multi-Agent Systems

In multi-agent systems, norm enforcement is a mechanism for steering the behavior of individual agents in order to achieve desired system-level objectives. Due to the dynamics of multi-agent systems, however, it is hard to design norms that guarantee the achievement of the objectives in every operating context. Also, these objectives may change over time, thereby making previously defined norms ineffective. In this paper, we investigate the use of system execution data to automatically synthesise and revise conditional prohibitions with deadlines, a type of norms aimed at prohibiting agents from exhibiting certain patterns of behaviors. We propose DDNR (Data-Driven Norm Revision), a data-driven approach to norm revision that synthesises revised norms with respect to a data set of traces describing the behavior of the agents in the system. We evaluate DDNR using a state-of-the-art, off-the-shelf urban traffic simulator. The results show that DDNR synthesises revised norms that are significantly more accurate than the original norms in distinguishing adequate and inadequate behaviors for the achievement of the system-level objectives.

Creating a Modeling Language Based on a New Metamodel for Adaptive Normative Software Agents

The demand for creating increasingly dynamic, autonomous and proactive software systems is challenging for the traditional Multi-agent Systems (MASs) approaches. Such requirement has given rise to adaptive software agents approaches. At the same time, norm is an essential and challenging feature that still tends to be addressed in adaptive MAS. In fact, norms to regulate agent behavior is still a vague concept that has not been properly investigated in terms of modeling and implementation. Even though many researchers have proposed modeling languages to deal with different abstractions, these languages fail to support the modeling of abstractions, such as adaptation and norms. Even more severe is the fact that little has been done to support the systematic design of Adaptive Normative Multi-Agent Systems (ANMASs). To facilitate the design and development of ANMASs, this paper presents a new metamodel, as well as language support, as means to provide tools to enable software developers. The proposed metamodel fosters a better understanding of the way agents are able to change their behaviors to deal with norms and captures interactions between agent’s norms and adaptation. To this end, our research is organized into five steps: (i) a literature review to identify the limitations of existing approaches related to ANMAS modeling; (ii) propose a new metamodel to support adaptative and normative concepts; (iii) propose a new language for modeling ANMASs; (iv) perform a qualitative and quantitative evaluation of the proposed language using a real case scenario, and (v) an empirical evaluation. The proposed metamodel and its associated modeling language advances the state of the art in modeling MASs and the approach is assessed in terms of correctness, time and difficulty. Our initial results revealed that our approach can be feasibly applied in a real world application, and is less difficult to apply and requires less time in comparison with a traditional approach. As software applications become more dynamic and adaptive, we believe it is essential to support developers to model MASs with abstractions such as adaptive agents, norms and their relationships. Such information can be foundational to steer future research on modeling adaptive agents capable of understanding and dealing with norms and adaptation.

Conceptual Model Based on Normative Multi-Agent System for Supply Chain Integration of Brazilian Gypsum LPA

The Brazilian gypsum has one of the highest levels of recognized mineral qualities in the world. Companies that operate in this sector support major economy-driving industries such as civil construction, architecture, medicine, and agriculture and are an input for the manufacture of paints, phosphors, and insecticides, among others. Most of the companies that constitute this sector are small and medium-sized enterprises (SMEs), which require supply chain solutions to maintain competition in market share. Supply chain integration as a collaborative solution has become a necessary strategy for enhancing SMEs decision-making capability. This study proposes a conceptual model based on a normative multi-agent system approach that offers a dynamic view about supply chain integration for managers and other stakeholders. From this contribution, it is possible to obtain constant information flow among stakeholders and build an effective strategic context for SMEs in the Brazilian Gypsum Local Productive Arrangement (LPA).

Nova : Value-based Negotiation of Norms

Specifying a normative multiagent system (nMAS) is challenging, because different agents often have conflicting requirements. Whereas existing approaches can resolve clear-cut conflicts, tradeoffs might occur in practice among alternative nMAS specifications with no apparent resolution. To produce an nMAS specification that is acceptable to each agent, we model the specification process as a negotiation over a set of norms. We propose an agent-based negotiation framework, where agents’ requirements are represented as values (e.g., patient safety, privacy, and national security), and an agent revises the nMAS specification to promote its values by executing a set of norm revision rules that incorporate ontology-based reasoning. To demonstrate that our framework supports creating a transparent and accountable nMAS specification, we conduct an experiment with human participants who negotiate against our agent. Our findings show that our negotiation agent reaches better agreements (with small p -value and large effect size) faster than a baseline strategy. Moreover, participants perceive that our agent enables more collaborative and transparent negotiations than the baseline (with small p -value and large effect size in particular settings) toward reaching an agreement.

Normative Emotional Agents: A Viewpoint Paper

Human social relationships imply conforming to the norms, behaviors, and cultural values of the society, but also socialization of emotions, to learn how to interpret and show them. In multiagent systems, much progress has been made in the analysis and interpretation of both emotions and norms. Nonetheless, the relationship between emotions and norms has hardly been considered and most normative agents do not consider emotions, or vice-versa. In this article, we provide an overview of relevant aspects within the area of normative agents and emotional agents. First we focus on the concept of norm, the different types of norms, its life cycle and a review of multiagent normative systems. Second, we present the most relevant theories of emotions, the life cycle of an agent’s emotions, and how emotions have been included through computational models in multiagent systems. Next, we present an analysis of proposals that integrate emotions and norms in multiagent systems. From this analysis, four relationships are detected between norms and emotions, which we analyze in detail and discuss how these relationships have been tackled in the reviewed proposals. Finally, we present a proposal for an abstract architecture of a Normative Emotional Agent that covers these four norm-emotion relationships.

Runtime revision of sanctions in normative multi-agent systems

To achieve system-level properties of a multiagent system, the behavior of individual agents should be controlled and coordinated. One way to control agents without limiting their autonomy is to enforce norms by means of sanctions. The dynamicity and unpredictability of the agents’ interactions in uncertain environments, however, make it hard for designers to specify norms that will guarantee the achievement of the system-level objectives in every operating context. In this paper, we propose a runtime mechanism for the automated revision of norms by altering their sanctions. We use a Bayesian Network to learn, from system execution data, the relationship between the obedience/violation of the norms and the achievement of the system-level objectives. By combining the knowledge acquired at runtime with an estimation of the preferences of rational agents, we devise heuristic strategies that automatically revise the sanctions of the enforced norms. We evaluate our heuristics using a traffic simulator and we show that our mechanism is able to quickly identify optimal revisions of the initially enforced norms.

NorMAS-ML: Supporting the Modeling of Normative Multi-agent Systems

Context: A normative multi-agent system (NMAS) is composed of agents that their behavior is regulated by norms. The modeling of those elements (agents and norms) together at design time can be a good way for a complete understanding of their structure and behavior. Multi-agent system modeling language (MAS-ML) supports the representation of NMAS entities, but the support for concepts related to norms is somewhat limited. MAS-ML is founded in taming agents and objects (TAO) framework and has a support tool called the MAS-ML tool. Goal: The present work aims to present a UML-based modeling language called normative multi-agent system (NorMAS-ML) able to model the MAS main entities along with the static normative elements. Method: We extend the TAO adding normative concepts and spread out those concepts in two syntaxes of MAS-ML. Either abstract, adding or updating metaclasses and stereotypes or concrete, defining new graphic elements for representing the elements defined in the abstract syntax. Besides, we evolve the MAS-ML tool, considering the extension of MAS-ML by the model-driven approach. Results: NorMAS-ML, the new version of MAS-ML, allows a complete view of NMAS entities and has a support tool called NorMAS-ML tool. Beyond the definition of NorMAS-ML and its tool, we generate a new static diagram called “norm diagram” supported by the NorMAS-ML tool. In order to illustrate the syntax of NorMAS-ML, the entities of a conference management system and its norms are modeled jointly. Conclusion: NorMAS-ML can help software designers (i) to understand the properties and behavior of NMAS entities and (ii) to provide a software modeling following the stakeholders’ need and less complex for the development phase.

Understanding Hohfeld and Formalizing Legal Rights: The Hohfeldian Conceptions and Their Conditional Consequences

Hohfeld’s analysis (Fundamental Legal Conceptions as Applied in Judicial Reasoning, 1913, 1917) on the different types of rights and duties is highly influential in analytical legal theory, and it is considered as a fundamental theory in AI&Law and normative multi-agent systems. Yet a century later, the formalization of this theory remains, in various ways, unresolved. In this paper I provide a formal analysis of how the working of a system containing Hohfeldian rights and duties can be delineated. This formalization starts from using the same tools as the classical ones by Kanger and Lindahl used, but instead of focusing on the algebraic features of rights and duties, it aims at providing a comprehensive analysis of what these rights and duties actually are and how they behave and at saying something substantial on Power too—maintaining all along the Hohfeldian intentions that these rights and duties are sui generis and inherently relational.

NorJADE

Normative multi-agent systems are multi-agent systems where agents are governed by norms. This recent research domain is now in full expansion. Despite the progress made in this area, various challenges remain the subject of research studies. In particular, there is a need for innovative solutions to support the implementation of this kind of multi-agent systems in order to improve the development process and consequently to simplify the developers' task. In the literature, most proposed works in this area are either closely related to specific problems or require complicated theoretical frameworks. In this article, a new framework baptized NorJADE is proposed to support the implementation of normative multi-agent systems. The proposed framework is open source, simple, modular and extensible. It is based on the popular open source JADE platform and uses the two well-known software technologies: ontology and aspect-oriented programming. The framework and the associated tool are illustrated using a concrete case study.

Non-Functional Norms Specification and Verification Approach for Normative Multi-agents Systems

Normative Multi-agent system (NMAS) forms a promising approach to software engineering for the development of autonomous systems, in norms-based environments. During the construction of these systems, different requirements can be considered: functional and non-functional requirement. Existing research in NMAS have mostly focused on the study of functional and behavioral requirements specification and verification, while Non-Functional Requirements (NFR) are crucial in the development of systems. They have dealt with the NFR implicitly through the capabilities of functional requirements. An important research issue refers to NFR in NMAS, i.e. how to specify and enforce NFR in NMAS that involves heterogeneous and autonomous agents. The NFR define constraints for the system and specify the qualities that a system can have, for example, security, performance, reliability, comfort, availability. Also, NFR might conflict among each other (for example, cost and quality, comfort and economy). A conflict between two NFR occurs when the fulfillment of one NFR violates another NFR. One of the main challenges currently faced in NMAS research is that of NFR specification and verification. In particular, how to specify and verify NFR in autonomous systems? In this paper, we propose a normative approach that allows the specification and verification of NFR for autonomous systems. To do this, we propose a new type of norms, called Non-Functional Norms (NFN). Indeed, our approach provides (i) a BNF normative language for specifying NFN, and (ii) a mechanism, based on Constraint Satisfaction Problem (CSP) technique, for the detection and resolution of normative conflicts. Our normative approach is also illustrated by a case study describing Smart City Management System (SCMS).

Towards the Formalization of Contradictions in a Legal Multiagent System

As existing legal systems expand and become more complex, the search of effective ways to model them becomes increasingly important in the area of Computational Law. We chose normative multiagent systems (NMAS) to study the interaction between a legal framework, a set of agents and the fundamental theories that regulate the legal dynamics of a society. Using this approach in conjunction with Computational Tree Logic (CTL), we determined that there is an increasing possibility of encountering contradictions inside complex legal systems, which in turn could undermine their purposes. We consider that contradictions are the fundamental units to take into account when diagnosing a legal system, and we classify them into several kinds according to the system structure they affect. Finally, we point to the direction of research needed for the development of intelligent agents capable of targeting contradictions.

Conflict Detection among Multiple Norms in Multi-Agent Systems

ABSTRACTIn open multi-agent systems (MAS), norms are being used to regulate the behavior of the autonomous, heterogeneous and independently designed agents. One of the main challenges on developing normative systems is that norms may be in conflict with each other. Norms are in conflict when the fulfillment of one norm violates the other and vice-versa. In previous works, the conflict checkers consider that conflicts can be detected by simply analyzing pairs of norms. However, there may be conflicts that can only be detected when we analyze several norms together. This work presents a conflict checker capable to detect conflicts between two or more norms at the same time. A new, more expressive normative language, represented by a BNF grammar, was developed to define norms and Conflict Checker was implemented in tool format. Two validation principles were applied: software testing and formal verification. The strategy thus developed emerges as a new syntax for definition and verification of conflicts in MAS.

Fine-Grained Access Control via Policy-Carrying Data

We address the problem of associating access policies with datasets and how to monitor compliance via policy-carrying data. Our contributions are a formal model in first-order logic inspired by normative multi-agent systems to regulate data access, and a computational model for the validation of specific use cases and the verification of policies against criteria. Existing work on access policy identifies roles as a key enabler, with which we concur, but much of the rest focusses on authentication and authorization technology. Our proposal aims to address the normative principles put forward in Berners-Lee’s bill of rights for the internet, through human-readable but machine-processable access control policies.

Norms and value based reasoning: justifying compliance and violation

There is an increasing need for norms to be embedded in technology as the widespread deployment of applications such as autonomous driving, warfare and big data analysis for crime fighting and counter-terrorism becomes ever closer. Current approaches to norms in multi-agent systems tend either to simply make prohibited actions unavailable, or to provide a set of rules (principles) which the agent is obliged to follow, either as part of its design or to avoid sanctions and punishments. In this paper we argue for the position that agents should be equipped with the ability to reason about a system’s norms, by reasoning about the social and moral values that norms are designed to serve; that is, perform the sort of moral reasoning we expect of humans. In particular we highlight the need for such reasoning when circumstances are such that the rules should arguably be broken, so that the reasoning can guide agents in deciding whether to comply with the norms and, if violation is desirable, how best to violate them. One approach to enabling this is to make use of an argumentation scheme based on values and designed for practical reasoning: arguments for and against actions are generated using this scheme and agents choose between actions based on their preferences over these values. Moral reasoning then requires that agents have an acceptable set of values and an acceptable ordering on their values. We first discuss how this approach can be used to think about and justify norms in general, and then discuss how this reasoning can be used to think about when norms should be violated, and the form this violation should take. We illustrate how value based reasoning can be used to decide when and how to violate a norm using a road traffic example. We also briefly consider what makes an ordering on values acceptable, and how such an ordering might be determined.

Kont: Computing Tradeoffs in Normative Multiagent Systems

We propose Kont, a formal framework for comparing normative multiagent systems (nMASs) by computing tradeoffs among liveness (something good happens) and safety (nothing bad happens). Safety-focused nMASs restrict agents' actions to avoid undesired enactments. However, such restrictions hinder liveness, particularly in situations such as medical emergencies. We formalize tradeoffs using norms, and develop an approach for understanding to what extent an nMAS promotes liveness or safety. We propose patterns to guide the design of an nMAS with respect to liveness and safety, and prove their correctness. We further quantify liveness and safety using heuristic metrics for an emergency healthcare application. We show that the results of the application corroborate our theoretical development.

Group Norms for Multi-Agent Organisations

Normative multi-agent systems offer the ability to integrate social and individual factors to provide increased levels of fidelity with respect to modelling social phenomena, such as cooperation, coordination, group decision making, and organization, in both human and artificial agent systems. An important open research issue refers to group norms, that is, norms that govern groups of agents. Depending on the interpretation, group norms may be intended to affect the group as a whole, each member of a group, or some members of the group. Moreover, upholding group norms may require coordination among the members of the group. We have identified three sets of agents affected by group norms, namely, (i) the addressees of the norm, (ii) those that will act on it, and (iii) those that are responsible for ensuring norm compliance. We present a formalism to represent these, connecting it to a minimalist agent organisation model. We use our formalism to develop a reasoning mechanism that enables agents to identify their position with respect to a group norm to further support agent autonomy and coordination when deciding on possible courses of action.

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

This paper highlights the use of situated artificial institution (SAI) within a hybrid, interactive, normative multi-agent system to regulate human collaboration in crisis management. Norms regulate the actions of human actors based on the dynamics of the environment in which they are situated. This dynamics results from both environment evolution and actors’ actions. Our objective is to situate norms in the environment in order to provide a context-aware crisis regulation. However, this coupling must be a loose one to keep both levels independent and easyto-change in order to face the complex and changing crisis situations. To that aim, we introduce a constitutive level between environmental and normative states providing a loose coupling of normative regulation with environment evolution. Norms are thus no more referring to environmental facts but to status functions, i.e., the institutional interpretation of environmental facts through constitutive rules. We present how this declarative and distinct SAI modelling succeeds in managing the crisis with a context-aware crisis regulation.