ProMoca: Probabilistic Modeling and Analysis of Agents in Commitment Protocols

Günay, Akın; Liu, Yang; Zhang, Jie

doi:10.1613/jair.5135

Cited by 9 publications

(7 citation statements)

References 39 publications

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“…Given the importance of the concepts, it is no surprise that researchers, e.g., Chopra, Dalpiaz, Giorgini, and Mylopoulos (2010a); Günay, Liu, and Zhang (2016); Meneguzzi, Telang, and Singh (2013), have begun tying the concepts of goals and commitments together. We go beyond existing work by developing a foundational, formal approach.…”

Section: Introductionmentioning

confidence: 99%

A Coupled Operational Semantics for Goals and Commitments

Telang

Singh²,

Yorke-Smith³

2019

jair

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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.

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Section: Introductionmentioning

confidence: 99%

A Coupled Operational Semantics for Goals and Commitments

Telang

Singh²,

Yorke-Smith³

2019

jair

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“…Günay et al [35] share a similar spirit to our work, in that they too are motivated to analyse agents behaviours in commitment protocols. Their ProMoca framework models agent beliefs, goals, and commitments.…”

Section: Related Workmentioning

confidence: 81%

“…Of course, any party may represent a commitment internally but the meaning and significance of commitments derives from their relational nature. Over the years, there has been progress on structuring interactions in terms of commitment protocols [7,8,19,20,25,35,69]. Commitment protocols offer a noted advantage in that they enable participating agents to coordinate in a flexible manner, retaining their autonomy.…”

Section: Introductionmentioning

confidence: 99%

GoCo: planning expressive commitment protocols

Meneguzzi

Magnaguagno

Singh

et al. 2018

Auton Agent Multi-Agent Syst

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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 Multi-Agent Syst (2018) 32:459-502 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.

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“…Related Work. The literature on protocols for the commitment lifecycle focuses on (awareness of) the progression of agents' joint commitment's status, including whether some have been abandoned to pursue more valuable goals (Desai, Narendra, and Singh 2008;Günay, Liu, and Zhang 2016;Pereira, Oren, and Meneguzzi 2017). We focus just on the "detached" stage where an agreed-upon commitment is being actively pursued, and the pursuit requires a sequence of actions, where some might not have desired outcomes, or an agent's priorities could change in the midst of executing the sequence.…”

Section: Introductionmentioning

confidence: 99%

Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement

Zhang

Durfee

Singh

2020

AAAI

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Most research on probabilistic commitments focuses on commitments to achieve enabling preconditions for other agents. Our work reveals that probabilistic commitments to instead maintain preconditions for others are surprisingly harder to use well than their achievement counterparts, despite strong semantic similarities. We isolate the key difference as being not in how the commitment provider is constrained, but rather in how the commitment recipient can locally use the commitment specification to approximately model the provider's effects on the preconditions of interest. Our theoretic analyses show that we can more tightly bound the potential suboptimality due to approximate modeling for achievement than for maintenance commitments. We empirically evaluate alternative approximate modeling strategies, confirming that probabilistic maintenance commitments are qualitatively more challenging for the recipient to model well, and indicating the need for more detailed specifications that can sacrifice some of the agents' autonomy.

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ProMoca: Probabilistic Modeling and Analysis of Agents in Commitment Protocols

Cited by 9 publications

References 39 publications

A Coupled Operational Semantics for Goals and Commitments

A Coupled Operational Semantics for Goals and Commitments

GoCo: planning expressive commitment protocols

Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement

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