Social commitments are recognized as an abstraction that enables flexible coordination between autonomous agents. We make these contributions. First, we introduce and formalize a concept of a maintenance commitment, a kind of social commitment characterized by a maintenance condition whose truthhood an agent commits to maintain. This concept of maintenance commitments enables us to capture a richer variety of real-world scenarios than possible using achievement commitments with a temporal condition. Second, we develop a rule-based operational semantics, by which we study the relationship between agents' achievement and maintenance goals, achievement commitments, and maintenance commitments. Third, we motivate a notion of coherence between an agents' achievement and maintenance cognitive and social constructs, and prove that, under specified conditions, the goals and commitments of both rational agents individually and of a multiagent system altogether are coherent. Fourth, we illustrate our approach with a detailed real-world scenario from an aerospace aftermarket domain.@en

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.@en

This article introduces some of the key concepts and challenges pertaining to ethics from the standpoint of Internet applications.@en

The surprising capabilities demonstrated by AI technologies overlaid on detailed data and fine-grained control give cause for concern that agents can wield enormous power over human welfare, drawing increasing attention to ethics in AI. @en

Synchronous, face-to-face interactions such as brainstorming are considered essential for creative tasks (the old normal). However, face-to-face interactions are difficult to arrange because of the diverse locations and conflicting availability of people - a challenge made more prominent by work-from-home practices during the COVID-19 pandemic (the new normal). In addition, face-to-face interactions are susceptible to cognitive interference. We employ crowdsourcing as an avenue to investigate creativity in asynchronous, online interactions. We choose product ideation, a natural task for the crowd since it requires human insight and creativity into what product features would be novel and useful. We compare the performance of solo crowd workers with asynchronous teams of crowd workers formed without prior coordination. Our findings suggest that, first, crowd teamwork yields fewer but more creative ideas than solo crowdwork. The enhanced team creativity results when Second, cognitive interference, known to inhibit creativity in face-to-face teams, may not be significant in crowd teams. Third, teamwork promotes better achievement emotions for crowd workers. These findings provide a basis for trading off creativity, quantity, and worker happiness in setting up crowdsourcing workflows for product ideation. @en

This article addresses the challenge of planning coordinated activities for a set of autonomous agents, who coordinate according to social commitments among themselves. We develop a multi-agent plan in the form of a commitment protocol that allows the agents to coordinate in a flexible manner, retaining their autonomy in terms of the goals they adopt so long as their actions adhere to the commitments they have made. We consider an expressive first-order setting with probabilistic uncertainty over action outcomes. We contribute the first practical means to derive protocol enactments which maximise expected utility from the point of view of one agent. Our work makes two main contributions. First, we show how Hierarchical Task Network planning can be used to enact a previous semantics for commitment and goal alignment, and we extend that semantics in order to enact first-order commitment protocols. Second, supposing a cooperative setting, we introduce uncertainty in order to capture the reality that an agent does not know for certain that its partners will successfully act on their part of the commitment protocol. Altogether, we employ hierarchical planning techniques to check whether a commitment protocol can be enacted efficiently, and generate protocol enactments under a variety of conditions. The resulting protocol enactments can be optimised either for the expected reward or the probability of a successful execution of the protocol. We illustrate our approach on a real-world healthcare scenario.@en

Ethics is inherently a multiagent concern. However, research on AI ethics today is dominated by work on individual agents: (1) how an autonomous robot or car may harm or (differentially) benefit people in hypothetical situations (the so-called trolley problems) and (2) how a machine learning algorithm may produce biased decisions or recommendations. The societal framework is largely omitted. To develop new foundations for ethics in AI, we adopt a sociotechnical stance in which agents (as technical entities) help autonomous social entities or principals (people and organizations). This multiagent conception of a sociotechnical system (STS) captures how ethical concerns arise in the mutual interactions of multiple stakeholders. These foundations would enable us to realize ethical STSs that incorporate social and technical controls to respect stated ethical postures of the agents in the STSs. The envisioned foundations require new thinking, along two broad themes, on how to realize (1) an STS that reflects its stakeholders’ values and (2) individual agents that function effectively in such an STS.@en

We address the problem of designing agents that navigate social norms by selecting ethically appropriate actions. We present Elessar, a framework in which agents aggregate value preferences of users and select ethically appropriate actions through multicriteria decision making in different social contexts. Via simulations, seeded with a survey of user values and attitudes, we find that Elessar agents act ethically and are effective than baseline agents, in terms of (1) exhibiting the Rawlsian property of fairness, and (2) yielding a satisfactory social experience to users. Our results are stable across agent societies of different sizes and connectedness.@en

As smart cities increasingly become real, an ethical framework for them becomes increasingly necessary. Surprisingly, current approaches largely disregard such a framework and concentrate primarily on challenges pertaining to the data lifecycle. However, a smart city involves much more than data gathering: it involves the interactions of residents, businesses, and government agencies with respect to public and private resources subject to potentially subtle regulations and other norms. This article introduces a sociotechnical view of smart cities and shows how it may be profitably mapped to the moral foundation theory to provide a comprehensive ethical framework.@en

We introduce and formalize a concept of a maintenance commitment, a kind of social commitment characterized by states whose truthhood an agent commits to maintain. This concept of maintenance commitments enables us to capture a richer variety of real-world scenarios than possible using achievement commitments with a temporal condition. By developing a rule-based operational semantics, we study the relationship between agents' achievement and maintenance goals, achievement commitments, and maintenance commitments. We motivate a notion of coherence which captures alignment between an agents' achievement and maintenance cognitive and social constructs, and prove that, under specified conditions, the goals and commitments of both rational agents individually and of a multiagent system are coherent.@en

Commitments capture how an agent relates to another agent, whereas goals describe states of the world that an agent is motivated to bring about. Commitments are elements of the social state of a set of agents whereas goals are elements of the private states of individual agents. It makes intuitive sense that goals and commitments are understood as being complementary to each other. More importantly, an agent’s goals and commitments ought to be coherent, in the sense that an agent’s goals would lead it to adopt or modify relevant commitments and an agent’s commitments would lead it to adopt or modify relevant goals. However, despite the intuitive naturalness of the above connections, they have not been adequately studied in a formal framework. This article provides a combined operational semantics for goals and commitments by relating their respective life cycles as a basis for how these concepts (1) cohere for an individual agent and (2) engender cooperation among agents. Our semantics yields important desirable properties of convergence of the configurations of cooperating agents, thereby delineating some theoretically well-founded yet practical modes of cooperation in a multiagent system.@en