Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Tosca: Operationalizing Commitments Over Information Protocols
Authors: Thomas C. King, Akın Günay, Amit K. Chopra, Munindar P. Singh
IJCAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | 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. ... Tosca's contribution is a method for automatically synthesizing the appropriate protocol. ... Tosca gives a method for ensuring progress toward alignment. Specifically, given a BSPL protocol and a set of commitments defined over the messages in the protocol, it gives a method for synthesizing a BSPL protocol whose enactment guarantees progress toward alignment. Furthermore, if the input protocol is live and safe, the synthesized protocol is live and safe as well. |
| Researcher Affiliation | Academia | 1Lancaster University, Lancaster, LA1 4WA, United Kingdom 2North Carolina State University, Raleigh, NC 27695-8206, USA EMAIL, EMAIL |
| Pseudocode | Yes | Listing 1: A BSPL protocol for placing and fulfilling orders. ... Listing 2: A specification in Cupid s surface syntax. ... Listing 9: A partial alignment protocol for the Escrow Purchase commitment in Listing 4 |
| Open Source Code | No | The paper does not provide any explicit statement or link regarding the availability of open-source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not utilize datasets for training or evaluation; therefore, no information on publicly available datasets is provided. |
| Dataset Splits | No | The paper describes a theoretical framework and does not include empirical validation with dataset splits. |
| Hardware Specification | No | The paper focuses on theoretical contributions and does not describe any specific hardware used for experiments or development. |
| Software Dependencies | No | The paper mentions BSPL and Cupid as languages for specification, but does not list any specific software dependencies (e.g., libraries, compilers, or tools) with version numbers. |
| Experiment Setup | No | The paper presents a theoretical framework and formalisms; it does not include an experimental setup with hyperparameters or training configurations. |