Nirav Ajmeri

AAMAS Conference 2026 Conference Paper

Guiding Sociotechnical Systems toward Value-Norm Equilibrium

• Nirav Ajmeri
• Marina De Vos
• Davide Dell'Anna
• Pradeep K. Murukannaiah
• Vivek Nallur
• Luis G. Nardin
• Munindar P. Singh

Values and norms are complementary constructs that undergird prosocialbehaviorinsociotechnicalsystems(STSs). Whereasvalues are intrinsic motivators for prosocial behavior, norms are extrinsic motivators for meeting mutual expectations. An STS is in equilibrium when the values of its member actors and the norms that govern it align with each other. Such an equilibrium is not permanent as actors join or leave the STS, and their values and norms evolve. In general, an STS must be guided toward equilibrium by systematically refining the norm specifications and influencing the values of its member actors. We formulate the challenges involved in building systematic methods to detect misalignment and guide the STS toward, and maintain, value-norm equilibrium.

AAAI Conference 2026 Short Paper

Language Models Do Not Embed Numbers Continuously (Student Abstract)

• Alex Davies
• Roussel Nzoyem Ngueguin
• Nirav Ajmeri
• Telmo de Menezes E Silva Filho

We evaluate how well large language model embeddings represent continuous numerical values across different precisions and ranges. Using linear models and principal component analysis on models from major providers, we show that while embeddings can reconstruct numbers with high fidelity (R2 ≥ 0.95), they introduce substantial noise, with principal components explaining less than 40% of embedding variance. Performance degrades with increasing decimal precision and mixed-sign values, revealing fundamental limitations in how these models encode numerical information.

AAMAS Conference 2025 Conference Paper

Combining Normative Ethics Principles to Learn Prosocial Behaviour

• Jessica Woodgate
• Nirav Ajmeri

Principles from normative ethics—the philosophical study of morality—can be operationalised in the decision-making capacities of agents to discern ethically acceptable actions and promote prosocial behaviour, defined as behaviours that support the well-being of others. Challenges exist in operationalising principles: (1) individual principles may be unintuitive; (2) while incorporating multiple principles mitigates issues with individual principles, conflicts may arise between them. We present PriENE, a method for combining multiple principles to encourage agents to learn prosocial behaviour.

AAAI Conference 2025 Conference Paper

Operationalising Rawlsian Ethics for Fairness in Norm Learning Agents

• Jessica Woodgate
• Paul Marshall
• Nirav Ajmeri

Social norms are standards of behaviour common in a society. However, when agents make decisions without considering how others are impacted, norms can emerge that lead to the subjugation of certain agents. We present RAWL·E, a method to create ethical norm-learning agents. RAWL·E agents operationalise maximin, a fairness principle from Rawlsian ethics, in their decision-making processes to promote ethical norms by balancing societal well-being with individual goals. We evaluate RAWL·E agents in simulated harvesting scenarios. We find that norms emerging in RAWL·E agent societies enhance social welfare, fairness, and robustness, and yield higher minimum experience compared to those that emerge in agent societies that do not implement Rawlsian ethics.

KER Journal 2024 Journal Article

Artificial intelligence for collective intelligence: a national-scale research strategy

• Seth Bullock
• Nirav Ajmeri
• Mike Batty
• Michaela Black
• John Cartlidge
• Robert Challen
• Cangxiong Chen
• Jing Chen

Abstract Advances in artificial intelligence (AI) have great potential to help address societal challenges that are both collective in nature and present at national or transnational scale. Pressing challenges in healthcare, finance, infrastructure and sustainability, for instance, might all be productively addressed by leveraging and amplifying AI for national-scale collective intelligence. The development and deployment of this kind of AI faces distinctive challenges, both technical and socio-technical. Here, a research strategy for mobilising inter-disciplinary research to address these challenges is detailed and some of the key issues that must be faced are outlined.

AAMAS Conference 2024 Conference Paper

Norm Enforcement with a Soft Touch: Faster Emergence, Happier Agents

• Sz-Ting Tzeng
• Nirav Ajmeri
• Munindar P. Singh

A multiagent system is a society of autonomous agents whose interactions can be regulated via social norms. In general, the norms of a society are not hardcoded but emerge from the agents’ interactions. Specifically, how the agents in a society react to each other’s behavior and respond to the reactions of others determines which norms emerge in the society. We think of these reactions by an agent to the satisfactory or unsatisfactory behaviors of another agent as communications from the first agent to the second agent. Understanding these communications is a kind of social intelligence: these communications provide natural drivers for norm emergence by pushing agents toward certain behaviors, which can become established as norms. Whereas it is well-known that sanctioning can lead to the emergence of norms, we posit that a broader kind of social intelligence can prove more effective in promoting cooperation in a multiagent system. Accordingly, we develop Nest, a framework that models social intelligence via a wider variety of communications and understanding of them than in previous work. To evaluate Nest, we develop a simulated pandemic environment and conduct simulation experiments to compare Nest with baselines considering a combination of three kinds of social communication: sanction, tell, and hint. We find that societies formed of Nest agents achieve norms faster. Moreover, Nest agents effectively avoid undesirable consequences, which are negative sanctions and deviation from goals, and yield higher satisfaction for themselves than baseline agents despite requiring only an equivalent amount of information.

ECAI Conference 2024 Conference Paper

Value-Based Rationales Improve Social Experience: A Multiagent Simulation Study

• Sz-Ting Tzeng
• Nirav Ajmeri
• Munindar P. Singh

We propose Exanna, a framework to realize agents that incorporate values in decision making. An Exanna agent considers the values of itself and others when providing rationales for its actions and evaluating the rationales provided by others. Via multiagent simulation, we demonstrate that considering values in decision making and producing rationales, especially for norm-deviating actions, leads to (1) higher conflict resolution, (2) better social experience, (3) higher privacy, and (4) higher flexibility.

AAMAS Conference 2022 Conference Paper

Macro Ethics for Governing Equitable Sociotechnical Systems

• Jessica Woodgate
• Nirav Ajmeri

The evolving relationship between humans and technology entails increasing concerns about the impact on ethical issues such as bias, unfairness, and lack of accountability. There is thus a need for consistent responses to multiple-user social dilemmas that arise during interactions in sociotechnical systems, where combinations of humans and technical agents work together as ethical duos. The outcomes of these systems can be evaluated by the values that participating humans hold, which in turn influence the development of norms used to guide acceptable behaviour. However, when values are misjudged or norms conflict, dilemmas arise that must be resolved in satisfactory ways. To examine these dilemmas, we adopt a macro ethics perspective where ethics is addressed via the governance of sociotechnical systems with multiple agents (rather than through the actions of single agents). We propose that to produce satisfactory outcomes, systematic methodologies be developed to consistently integrate normative ethical principles in reasoning capacities. The application of these ethical principles would enable practitioners to think analytically and systematically about the multiple-user social dilemmas that occur in these systems, in order to resolve them in satisfactory ways. To achieve this, we need to (1) categorize ethical principles not yet used in AI, form new ways of (2) systematically integrating ethical principles into reasoning, and use these new ways to (3) develop consistent responses to multiple-user social dilemmas.

TAAS Journal 2022 Journal Article

Prosocial Norm Emergence in Multi-agent Systems

• Mehdi Mashayekhi
• Nirav Ajmeri
• George F. List
• Munindar P. Singh

Multi-agent systems provide a basis for developing systems of autonomous entities and thus find application in a variety of domains. We consider a setting where not only the member agents are adaptive but also the multi-agent system viewed as an entity in its own right is adaptive. Specifically, the social structure of a multi-agent system can be reflected in the social norms among its members. It is well recognized that the norms that arise in society are not always beneficial to its members. We focus on prosocial norms, which help achieve positive outcomes for society and often provide guidance to agents to act in a manner that takes into account the welfare of others. Specifically, we propose Cha, a framework for the emergence of prosocial norms. Unlike previous norm emergence approaches, Cha supports continual change to a system (agents may enter and leave) and dynamism (norms may change when the environment changes). Importantly, Cha agents incorporate prosocial decision-making based on inequity aversion theory, reflecting an intuition of guilt arising from being antisocial. In this manner, Cha brings together two important themes in prosociality: decision-making by individuals and fairness of system-level outcomes. We demonstrate via simulation that Cha can improve aggregate societal gains and fairness of outcomes.

IJCAI Conference 2022 Conference Paper

Socially Intelligent Genetic Agents for the Emergence of Explicit Norms

• Rishabh Agrawal
• Nirav Ajmeri
• Munindar Singh

Norms help regulate a society. Norms may be explicit (represented in structured form) or implicit. We address the emergence of explicit norms by developing agents who provide and reason about explanations for norm violations in deciding sanctions and identifying alternative norms. These agents use a genetic algorithm to produce norms and reinforcement learning to learn the values of these norms. We find that applying explanations leads to norms that provide better cohesion and goal satisfaction for the agents. Our results are stable for societies with differing attitudes of generosity.

AAMAS Conference 2019 Conference Paper

Applying Norms and Sanctions to Promote Cybersecurity Hygiene

• Shubham Goyal
• Nirav Ajmeri
• Munindar P. Singh

Cybersecurity breaches cause enormous harm to the safety, privacy, and prosperity of individuals and organizations. Many security breaches occur due to people not following security regulations such as applying software patches, updating software applications, and so on. We term these regulations as cybersecurity hygiene. This paper investigates different sanctioning mechanisms with respect to the success in establishing these regulations for cybersecurity hygiene. Our findings have implications for workforce training to promote cybersecurity.

IJCAI Conference 2019 Conference Paper

The Interplay of Emotions and Norms in Multiagent Systems

• Anup K. Kalia
• Nirav Ajmeri
• Kevin S. Chan
• Jin-Hee Cho
• Sibel Adalı
• Munindar P. Singh

We study how emotions influence norm outcomes in decision-making contexts. Following the literature, we provide baseline Dynamic Bayesian models to capture an agent's two perspectives on a directed norm. Unlike the literature, these models are holistic in that they incorporate not only norm outcomes and emotions but also trust and goals. We obtain data from an empirical study involving game play with respect to the above variables. We provide a step-wise process to discover two new Dynamic Bayesian models based on maximizing log-likelihood scores with respect to the data. We compare the new models with the baseline models to discover new insights into the relevant relationships. Our empirically supported models are thus holistic and characterize how emotions influence norm outcomes better than previous approaches.

IJCAI Conference 2018 Conference Paper

Robust Norm Emergence by Revealing and Reasoning about Context: Socially Intelligent Agents for Enhancing Privacy

• Nirav Ajmeri
• Hui Guo
• Pradeep K. Murukannaiah
• Munindar P. Singh

Norms describe the social architecture of a society and govern the interactions of its member agents. It may be appropriate for an agent to deviate from a norm; the deviation being indicative of a specialized norm applying under a specific context. Existing approaches for norm emergence assume simplified interactions wherein deviations are negatively sanctioned. We investigate via simulation the benefits of enriched interactions where deviating agents share selected elements of their contexts. We find that as a result (1) the norms are learned better with fewer sanctions, indicating improved social cohesion; and (2) the agents are better able to satisfy their individual goals. These results are robust under societies of varying sizes and characteristics reflecting pragmatic, considerate, and selfish agents.

AAMAS Conference 2017 Conference Paper

Arnor: Modeling Social Intelligence via Norms to Engineer Privacy-Aware Personal Agents

• Nirav Ajmeri
• Pradeep K. Murukannaiah
• Hui Guo
• Munindar P. Singh

We seek to address the challenge of engineering socially intelligent personal agents that are privacy-aware. We propose Arnor, a method, including a metamodel based on social constructs. Arnor incorporates social norms and goes beyond existing agent-oriented software engineering (AOSE) methods by systematically capturing how a personal agent’s actions influence the social experience it delivers. We conduct two empirical studies to evaluate Arnor. First, via a multiphase developer study, we show that Arnor simplifies application development. Second, via simulation experiments, we show that Arnor provides improved privacy-preserving social experience to end users than personal agents engineered using a traditional AOSE method.

AAMAS Conference 2017 Conference Paper

Engineering Socially Intelligent Personal Agents via Norms

• Nirav Ajmeri

AAAI Conference 2017 Conference Paper

Kont: Computing Tradeoffs in Normative Multiagent Systems

• Ozgur Kafali
• Nirav Ajmeri
• Munindar Singh

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.

KER Journal 2016 Journal Article

Classifying sanctions and designing a conceptual sanctioning process model for socio-technical systems

• Luis G. Nardin
• Tina Balke-Visser
• Nirav Ajmeri
• Anup K. Kalia
• Jaime S. Sichman
• Munindar P. Singh

Abstract We understand a socio-technical system (STS) as a cyber-physical system in which two or more autonomous parties interact via or about technical elements, including the parties’ resources and actions. As information technology begins to pervade every corner of human life, STSs are becoming ever more common, and the challenge of governing STSs is becoming increasingly important. We advocate a normative basis for governance, wherein norms represent the standards of correct behaviour that each party in an STS expects from others. A major benefit of focussing on norms is that they provide a socially realistic view of interaction among autonomous parties that abstracts low-level implementation details. Overlaid on norms is the notion of a sanction as a negative or positive reaction to potentially any violation of or compliance with an expectation. Although norms have been well studied as regards governance for STSs, sanctions have not. Our understanding and usage of norms is inadequate for the purposes of governance unless we incorporate a comprehensive representation of sanctions. We address the aforementioned gap by proposing (i) a sanction typology that reflects the relevant features of sanctions, and (ii) a conceptual sanctioning process model providing a functional structure for sanctioning in STS. We demonstrate our contributions via a motivating scenario from the domain of renewable energy trading.

IJCAI Conference 2016 Conference Paper

Coco: Runtime Reasoning about Conflicting Commitments

• Nirav Ajmeri
• Jiaming Jiang
• Rada Chirkova
• Jon Doyle
• Munindar P. Singh

To interact effectively, agents must enter into commitments. What should an agent do when these commitments conflict? We describe Coco, an approach for reasoning about which specific commitments apply to specific parties in light of general types of commitments, specific circumstances, and dominance relations among specific commitments. Coco adapts answer-set programming to identify a maximal set of nondominated commitments. It provides a modeling language and tool geared to support practical applications.

IS Journal 2016 Journal Article

Revani: Revising and Verifying Normative Specifications for Privacy

• Ozgur Kafaly
• Nirav Ajmeri
• Munindar P. Singh

Privacy remains a major challenge today, partly because it brings together social and technical considerations. Yet, current software engineering focuses only on the technical aspects. In contrast, the authors' approach, Revani, understands privacy from the standpoint of sociotechnical systems (STSs), with particular attention on the social elements of STSs. They specify STSs via a combination of technical mechanisms and social norms founded on accountability. Revani provides a way to formally represent mechanisms and norms and applies model checking to verify whether specified mechanisms and norms would satisfy stakeholder requirements. Additionally, Revani provides a set of design patterns and a revision tool to update an STS specification as necessary. The authors demonstrate the work of Revani on a healthcare emergency use case pertaining to patient privacy during disasters.