Dynamically generated commitment protocols in open systems

Günay, Akın; Winikoff, Michael; Yolum, Pınar

doi:10.1007/s10458-014-9251-7

Cited by 20 publications

(11 citation statements)

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“…Günay et al [Günay et al, 2015] generate commitment specifications from requirements. We understand commitment specifications as requirements and synthesize operational protocol specifications.…”

Section: Discussionmentioning

confidence: 99%

Tosca: Operationalizing Commitments Over Information Protocols

King

Günay

Chopra

et al. 2017

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence

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The notion of commitment is widely studied as a high-level abstraction for modeling multiagent interaction. An important challenge is supporting flexible decentralized enactments of commitment specifications. In this paper, we combine recent advances on specifying commitments and information protocols. Specifically, we contribute Tosca, a technique for automatically synthesizing information protocols from commitment specifications. Our main result is that the synthesized protocols support commitment alignment, which is the idea that agents must make compatible inferences about their commitments despite decentralization.

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Section: Discussionmentioning

confidence: 99%

Tosca: Operationalizing Commitments Over Information Protocols

King

Günay

Chopra

et al. 2017

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence

Self Cite

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“…Such formal model-checking approaches have been applied to (pre-defined) commitment-based protocols. Günay et al [46] propose an algorithm for agents to generate novel protocols at runtime.…”

Section: Related Work and Discussionmentioning

confidence: 99%

Commitments and interaction norms in organisations

Dastani

Torre

Yorke-Smith

2015

Auton Agent Multi-Agent Syst

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In an organisational setting such as an online marketplace, an entity called the 'organisation' or 'institution' defines interaction protocols, monitors agent interaction, and intervenes to enforce the interaction protocols. The organisation might be a software system that thus regulates the marketplace, for example. In this article we abstract over applicationspecific protocols and consider commitment lifecycles as generic interaction protocols. We model interaction protocols by explicitly-represented norms, such that we can operationalise the enforcement of protocols by means of norm enforcement, and we can analyse the protocols by a logical analysis of the norms. We adopt insights and methods from commitment-based approaches to agent interaction as well as from norm-based approaches to agent behaviour governance. First, we show how to use explicitly-represented norms to model commitment dynamics (lifecycles). Second, we introduce an operational semantics to operationalise norm enforcement. Third, we show how to logically analyse interaction protocols by means of commitment dynamics and norm enforcement. The model, semantics, and analysis are illustrated by a running example from a vehicle insurance domain. Keywords Commitments · Normative organisations · Operational semanticsThe foundations of the ideas developed in this article were presented at the COIN workshop at AAMAS'12 [34] and briefly summarized at the AAMAS'12 conference [33].

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“…We would need to develop a methodology around the protocol languages that would support (1) refining stakeholder requirements into protocols, e.g., as in [39], [40]; (2) protocol verification tools, e.g., to verify safety and liveness of information protocols [34], [41] and to verify the satisfiability and falsifiability of norms [27]; (3) middleware to ensure correct decentralized enactment [42]; and (4) interaction-oriented programming models for agents, as described above. We term this overall methodology Interaction-Oriented Software Engineering (IOSE) [43] to distinguish it from Agent-Oriented Software Engineering (AOSE).…”

Section: B Interaction-oriented Software Engineeringmentioning

confidence: 99%

The Internet of Things and Multiagent Systems: Decentralized Intelligence in Distributed Computing

Singh

Chopra

2017

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)

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Abstract-Traditionally, distributed computing concentrates on computation understood at the level of information exchange and sets aside human and organizational concerns as largely to be handled in an ad hoc manner. Increasingly, however, distributed applications involve multiple loci of autonomy. Research in multiagent systems (MAS) addresses autonomy by drawing on concepts and techniques from artificial intelligence. However, MAS research generally lacks an adequate understanding of modern distributed computing.In this Blue Sky paper, we envision decentralized multiagent systems as a way to place decentralized intelligence in distributed computing, specifically, by supporting computation at the level of social meanings. We motivate our proposals for research in the context of the Internet of Things (IoT), which has become a major thrust in distributed computing. From the IoT's representative applications, we abstract out the major challenges of relevance to decentralized intelligence. These include the heterogeneity of IoT components; asynchronous and delay-tolerant communication and decoupled enactment; and multiple stakeholders with subtle requirements for governance, incorporating resource usage, cooperation, and privacy. The IoT yields high-impact problems that require solutions that go beyond traditional ways of thinking.We conclude with highlights of some possible research directions in decentralized MAS, including programming models; interaction-oriented software engineering; and what we term enlightened governance.

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Dynamically generated commitment protocols in open systems

Cited by 20 publications

References 20 publications

Tosca: Operationalizing Commitments Over Information Protocols

Tosca: Operationalizing Commitments Over Information Protocols

Commitments and interaction norms in organisations

The Internet of Things and Multiagent Systems: Decentralized Intelligence in Distributed Computing

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