Exploiting Social Commitments in Programming Agent Interaction

Baldoni, Matteo; Baroglio, Cristina; Capuzzimati, Federico; Micalizio, Roberto

doi:10.1007/978-3-319-25524-8_39

Cited by 4 publications

(2 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Third, in Sect. 4 we provide the complete extended formalisation of the commitment dynamics and reasoning patterns [63] underlying our verification system. Fourth, in Sect.…”

Section: -How Can An Agent Gain Assurance That Its Goals Are Indeed Amentioning

confidence: 99%

“…As with our work, Baldoni et al [4][5][6] use the commitment-goal semantics of Telang et al [63] as their starting point. These authors present an extension to the norm-and artefact-aware agent programming language, JaCaMo, in which Jason agents can interact while preserving their deliberative capabilities by exploiting commitment-based protocols.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

GoCo: planning expressive commitment protocols

Meneguzzi

Magnaguagno

Singh

et al. 2018

Auton Agent Multi-Agent Syst

View full text Add to dashboard Cite

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.

show abstract

“…Third, in Sect. 4 we provide the complete extended formalisation of the commitment dynamics and reasoning patterns [63] underlying our verification system. Fourth, in Sect.…”

Section: -How Can An Agent Gain Assurance That Its Goals Are Indeed Amentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%