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Muon: designing multiagent communication protocols from interaction scenarios

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Abstract

Designing a suitable communication protocol is a key challenge in engineering a multiagent system. This paper proposes Muon, an approach that begins from representative samples of interactions or scenarios. Muon identifies key semantic structures and patterns based on (social) commitments to formally analyze the scenarios and offers a methodology for designing protocols that would meet stakeholder needs. Interestingly, Muon applies its formal representations to suggest ways to identify additional scenarios needed to address exceptions arising in the interactions. This paper contributes (1) a conceptual model of message types and causal relationships among them as a foundation for developing commitment-based communication protocols; (2) a robust, reusable characterization of semantic structures reflecting the above model; (3) a mapping from an annotated scenario to causally related interactions; and (4) a methodology to synthesize specifications of communication protocols. This paper reports on an empirical evaluation involving developers creating protocols from two real-life cases.

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Acknowledgments

Special thanks to Ashok Mallya for early discussions that led to this work. Thanks to Amit Chopra, Nirmit Desai, Jon Doyle, Scott Gerard, Emerson Murphy-Hill, Pankaj Telang, and the anonymous reviewers for helpful comments. This work was partially supported by the NSF under Grant 0910868 and by the U.S. Army Research Office (ARO) under Grant W911NF-08-1-0105 managed by the NCSU Secure Open Systems Initiative.

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Authors and Affiliations

  1. North Carolina State University, Raleigh, NC, 27695-8206, USA

    Anup K. Kalia & Munindar P. Singh

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  1. Anup K. Kalia
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Correspondence to Anup K. Kalia.

Appendices

Appendix 1: A complete scenario

Step M4 yields a complete scenario containing the happy path and exception scenarios. Table 6 shows this complete scenario.

Table 6 A complete scenario for the AGFIL case
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Appendix 2: Empirical study details

1.1 The ASPE breast cancer diagnosis case

We provided the following passage to study subjects.

A patient (P) finds symptoms of breast cancer and reports a primary care physician (PCP). If the patient is new, PCP immediately starts examining the patient or else he collects the history of the patient before the examination. PCP thoroughly examine the breasts for lumps or suspicious areas. He then sends the patient to a radiologist (R) for a mammography or imaging. R performs a diagnostic imaging and reports the results to PCP. PCP reviews the results. If PCP finds P’s condition not worrisome, then he asks P to visit just for an yearly checkup. If PCP finds the P’s tumor benign, then he asks her to come back after four to six months. If PCP finds the tumor suspicious then he orders R for a biopsy. R performs a biopsy and forwards the tissue specimens to a pathologist (PT). PT accesses the specimen and conducts several laboratory examinations to determine the nature of the cancer and comes up with a report. PT then holds a conference with R and ensures their results are concordant. R then forwards the integrated reports produced by him and P to PCP. The registrar (RG) registers the patient under a breast cancer registry. PCP checks the integrated report. If the tissue sample is benign, the tumor is removed by a surgeon (S). If the sample is malignant, PCP discusses the treatment steps with P. P pays PCP for the checkup, imaging, and biopsy. PCP pays R for imaging and biopsy. R pays PT for preparing the biopsy report (Tables 7, 8, 9, 10, 11).

1.2 AGFIL automobile insurance case

We provided the following passage to study subjects.

AGF Irish Life Holdings (AG) is an insurer and covers the losses incurred by policy holders. John Doe (JD) is a policy holder. AG creates a policy with JD such that if JD pays the premium, AG will insure his car. JD pays the premium and gets his car insured. AG requests Europ Assist (EA) to receive claims from policy holders to which EA agrees. AG pays EA for receiving the claims. When JD meets with a car accident, he requests for a claim to EA. EA asks JD to take his car to a mechanic (M) and reports AG about the claim made by JD. AG hires Lee CS (LCS) for handling the claims made by JD. LCS offers M to pay if M estimates the repair costs for the JD’s car. When M provides the estimates, LCS verifies it. If the estimates are reasonable, he offers M to repair the car. When M repairs the car, LCS delegates the payment to AG. AG pays M for the repair and informs JD. JD gets his repaired car from M. AG pays EA for receiving the claims (Tables 12, 13, 14, 15).

1.3 Scenarios for the ASPE case

We provided the following happy path and exception scenarios to study subjects (Tables 16, 17, 18).

Table 7 The breast cancer case (happy path I)
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Table 8 The breast cancer case (exceptions I)
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Table 9 The breast cancer case (happy path II)
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Table 10 The breast cancer case (exceptions II)
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1.4 Scenarios for the AGFIL Case

We provided the following happy path and exception scenarios to study subjects (Tables 19, 20).

Table 11 The breast cancer case (happy path III)
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Table 12 The breast cancer case (exceptions III)
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Table 13 The breast cancer case (happy path IV)
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Table 14 The breast cancer case (exceptions IV)
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Table 15 I: A successful scenario for the AGFIL example
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Table 16 I: A scenario of exceptions for the AGFIL example
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Table 17 II: A successful scenario for the AGFIL example
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Table 18 II: A scenario of exceptions for the AGFIL example
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Table 19 III: A successful scenario for the AGFIL example
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Table 20 III: A scenario of exceptions for the AGFIL example
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Kalia, A.K., Singh, M.P. Muon: designing multiagent communication protocols from interaction scenarios. Auton Agent Multi-Agent Syst 29, 621–657 (2015). https://doi.org/10.1007/s10458-014-9264-2

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