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Thomas C. King

dblp:162/5028 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2017
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Multi-agent systems · 100%
Software engineering, system software, and programming languages
1 paper
Program synthesis and code generation · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program synthesis and code generation
specification synthesis
0.112017
Tosca: Operationalizing Commitments Over Information Protocols · IJCAI 2017

Methods — techniques the papers use, named apart from their topics

protocol synthesis · 0.6commitment specification · 0.6
YearPublicationVenuePosition
2017 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.
Thomas C. King, Akin Günay, Amit K. Chopra, Munindar P. Singh
IJCAI1