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Tosca: Operationalizing Commitments over Information Protocols

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Tosca: Operationalizing Commitments over Information Protocols. / King, Thomas Christopher; Günay, Akin; Chopra, Amit K. et al.
Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI). Melbourne: IJCAI, 2017. p. 256-264.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

King, TC, Günay, A, Chopra, AK & Singh, MP 2017, Tosca: Operationalizing Commitments over Information Protocols. in Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI). IJCAI, Melbourne, pp. 256-264. https://doi.org/10.24963/ijcai.2017/37

APA

King, T. C., Günay, A., Chopra, A. K., & Singh, M. P. (2017). Tosca: Operationalizing Commitments over Information Protocols. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI) (pp. 256-264). IJCAI. https://doi.org/10.24963/ijcai.2017/37

Vancouver

King TC, Günay A, Chopra AK, Singh MP. Tosca: Operationalizing Commitments over Information Protocols. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI). Melbourne: IJCAI. 2017. p. 256-264 doi: 10.24963/ijcai.2017/37

Author

King, Thomas Christopher ; Günay, Akin ; Chopra, Amit K. et al. / Tosca: Operationalizing Commitments over Information Protocols. Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI). Melbourne : IJCAI, 2017. pp. 256-264

Bibtex

@inproceedings{3473899db7154456aa0a3bd489c244db,
title = "Tosca: Operationalizing Commitments over Information Protocols",
abstract = "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.",
author = "King, {Thomas Christopher} and Akin G{\"u}nay and Chopra, {Amit K.} and Singh, {Munindar P.}",
year = "2017",
month = aug,
day = "23",
doi = "10.24963/ijcai.2017/37",
language = "English",
isbn = "9780999241103",
pages = "256--264",
booktitle = "Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI)",
publisher = "IJCAI",

}

RIS

TY - GEN

T1 - Tosca: Operationalizing Commitments over Information Protocols

AU - King, Thomas Christopher

AU - Günay, Akin

AU - Chopra, Amit K.

AU - Singh, Munindar P.

PY - 2017/8/23

Y1 - 2017/8/23

N2 - 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.

AB - 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.

U2 - 10.24963/ijcai.2017/37

DO - 10.24963/ijcai.2017/37

M3 - Conference contribution/Paper

SN - 9780999241103

SP - 256

EP - 264

BT - Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI)

PB - IJCAI

CY - Melbourne

ER -