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.

We address the problem of engineering a sociotechnical system (STS) with respect to its stakeholders’ requirements. We motivate a two-tier STS conception composed of a technical tier that provides control mechanisms and describes what actions are allowed by the software components, and a social tier that characterizes the stakeholders’ expectations of each other in terms of norms. We adopt agents as computational entities, each representing a different stakeholder. Unlike previous approaches, our framework, D ESEN , incorporates the social dimension into the formal verification process. Thus, D ESEN supports agents potentially violating applicable norms—a consequence of their autonomy. In addition to requirements verification, D ESEN supports refinement of STS specifications via design patterns to meet stated requirements. We evaluate D ESEN at three levels. We illustrate how D ESEN carries out refinement via the application of patterns on a hospital emergency scenario. We show via a human-subject study that a design process based on our patterns is helpful for participants who are inexperienced in conceptual modeling and norms. We provide an agent-based environment to simulate the hospital emergency scenario to compare STS specifications (including participant solutions from the human-subject study) with metrics indicating social welfare and norm compliance, and other domain dependent metrics.

We develop a novel strategy that supports software agents to make decisions on how to negotiate for a resource in open and dynamic e-markets. Although existing negotiation strategies offer a number of sophisticated features, including modelling an opponent and negotiating with many opponents simultaneously, they abstract away from the dynamicity of the market and the model that the agent holds for itself in terms of ongoing negotiations, thus ignoring information that increases an agent’s utility. Our proposed strategy COncurrent Negotiating AgeNts ( Conan ) considers a weighted combination of modelling the market environment and the progress of concurrent negotiations in which the agent partakes. We conduct extensive experiments to evaluate the strategy’s performance in various settings where different opponents from the literature provide a competitive market. Our experiments provide statistically significant results showing how Conan outperforms the state-of-the-art in terms of the utility gained during negotiations.

editorial Free Access Share on Guest Editors’ Introduction Authors: Özgür Kafali University of Kent, Canterbury, Kent, UK University of Kent, Canterbury, Kent, UKView Profile , Natalia Criado King’s College London, London, UK King’s College London, London, UKView Profile , Martin Rehak Cisco Systems, Czech Republic Cisco Systems, Czech RepublicView Profile , Jose M. Such King’s College London, London, UK King’s College London, London, UKView Profile , Pinar Yolum Utrecht University, Utrecht, Netherlands Utrecht University, Utrecht, NetherlandsView Profile Authors Info & Claims ACM Transactions on Internet TechnologyVolume 18Issue 3August 2018 Article No.: 26pp 1–4https://doi.org/10.1145/3177884Published:06 March 2018Publication History 0citation462DownloadsMetricsTotal Citations0Total Downloads462Last 12 Months21Last 6 weeks4 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

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.

Policy design is an important part of software development. As security breaches increase in variety, designing a security policy that addresses all potential breaches becomes a nontrivial task. A complete security policy would specify rules to prevent breaches. Systematically determining which, if any, policy clause has been violated by a reported breach is a means for identifying gaps in a policy. Our research goal is to help analysts measure the gaps between security policies and reported breaches by developing a systematic process based on semantic reasoning. We propose SEMAVER, a framework for determining coverage of breaches by policies via comparison of individual policy clauses and breach descriptions. We represent a security policy as a set of norms. Norms (commitments, authorizations, and prohibitions) describe expected behaviors of users, and formalize who is accountable to whom and for what. A breach corresponds to a norm violation. We develop a semantic similarity metric for pairwise comparison between the norm that represents a policy clause and the norm that has been violated by a reported breach. We use the US Health Insurance Portability and Accountability Act (HIPAA) as a case study. Our investigation of a subset of the breaches reported by the US Department of Health and Human Services (HHS) reveals the gaps between HIPAA and reported breaches, leading to a coverage of 65%. Additionally, our classification of the 1,577 HHS breaches shows that 44% of the breaches are accidental misuses and 56% are malicious misuses. We find that HIPAA's gaps regarding accidental misuses are significantly larger than its gaps regarding malicious misuses.

Abstract We present a knowledge representation framework on the basis of the Event Calculus that allows an agent to recognize complex activities from low‐level observations received by multiple sensors, reason about the life cycle of such activities, and take action to support their successful completion. Activities are multivalue fluents that change according to events that occur in the environment. The parameters of an activity consist of a unique label, a set of participants involved in the performing of the activity, and a unique goal associated with the activity revealing the activity's desired outcome. Our contribution is the identification of an activity life cycle describing how activities can be started, interrupted, suspended, resumed, or completed over time, as well as how these can be represented. The framework also specifies activity goals, their associated life cycle, and their relation with the activity life cycle. We provide the complete implementation of the framework, which includes an activity generator that automatically creates synthetic sensor data in the form of event streams that represent the everyday lifestyle of a type 1 diabetic patient. Moreover, we test the framework by generating very large activity streams that we use to evaluate the performance of the recognition capability and study its relative merits.

Recent data breaches in domains such as healthcare where confidentiality of data is crucial indicate that breaches often originate from misuses, not only from vulnerabilities in the technical (software or hardware) architecture. Current requirements engineering (RE) approaches determine what access control mechanisms are needed to protect sensitive resources (assets). However, current RE approaches inadequately characterize how a user is expected to interact with others in relation to the relevant assets. Consequently, a requirements analyst cannot readily identify misuses by legitimate users. We adopt social norms as a natural, formal means of characterizing user interactions whereby potential misuses map to norm violations. Our research goal is to help analysts identify misuse cases by formal reasoning about norm enactments. We propose Nane, a formal framework for identifying such misuse cases using a semiautomated process. We demonstrate how Nane enables monitoring of potential misuses on a healthcare scenario.

Goal-based agent architectures have been one of the most effective architectures for designing agents. In such architectures, the state of the agent as well as its goal set are represented explicitly. The agent then uses its set of actions to reach the goals in its goal set. However, in multiagent systems, most of the time, an agent cannot reach a goal only using its own actions but needs other agents to act as well. Commitments have been successfully used to regulate those interactions between agents. This paper proposes a framework and an environment for agents to manage the relations between their commitments and goals. More specifically, we provide an algorithm called GOSU to compute if a given set of commitments can be used to achieve a particular goal. We describe how GOSU can be implemented using the Reactive Event Calculus and demonstrate its capabilities over a case study.

We present Hydra: a multi-agent hybrid diagnosis and monitoring architecture that is aimed at helping diabetic patients manage their illness. It makes use of model-based diagnosis techniques, where the model can be developed by two different approaches combined in a novel way. In the first approach, we build the model based on the medical guidelines provided for diabetes. A computational logic agent monitors the patient and provides feedback based on the model whenever the current observations regarding the patient are sufficient to draw a conclusion. In the second approach, we assume a function for the model, and learn its parameters through data. The model is consistently updated via incoming observations about the patients, and allows prediction of possible future values. We describe the components of such an architecture, and how it can integrated into the existing COMMODITY12personal health system. We implement a prototype of Hydra, and present its workings on a case study on hypoglycemia monitoring. We report our prediction results for this scenario.

As online social networks are becoming part of both social and work life, preserving privacy of their users is becoming tremendously difficult. While these social networks are promising privacy through privacy agreements, everyday new privacy leakages are emerging. Ideally, online social networks should be able to manage and maintain their agreements through well-founded methods. However, the dynamic nature of the online social networks is making it difficult to keep private information contained. We have developed PROTOSS, a run time tool for detecting privacy leakages in online social networks. PROTOSS captures relations among users, their privacy agreements with an online social network operator, and domain-based inference rules. It then uses model checking to detect if an online social network will leak private information.

In open multiagent systems, agents need to model their environments in order to identify trustworthy agents. Models of the environment should be accurate so that decisions about whom to interact with can be done soundly. Traditional trust models are based on modeling specific properties of agents, such as their expertise or reliability. Building those models requires too many prior interactions to be accurate. This paper proposes an approach that is based on keeping track of outcomes of agent's actions towards others rather than modeling other agents' performances explicitly. Contrary to existing modeling approaches that require domain knowledge to build models, our proposed approach can be effectively realized in multiagent systems when the agent's actions are clearly identified. Comparisons with other modeling approaches in various environments reveal that our proposed approach can create more precise models in short time and can adjust its behavior quickly when other agents' behaviors change.