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Record W22166016 · doi:10.1021/nl204051v

Proceedings of the 2013 workshop on Programming based on actors, agents, and decentralized control

2013· article· en· W22166016 on OpenAlexaff
Nadeem Jamali, Alessandro Ricci, Gera Weiss, Akinori Yonezawa

Bibliographic record

VenueACM conference on Systems, Programming, Languages and Applications: Software for Humanity · 2013
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsUniversity of Saskatchewan
FundersNational Cancer Institute
KeywordsComputer scienceConcurrent object-oriented programmingProgramming paradigmConcurrencyMainstreamPopularitySoftware engineeringDistributed computingReactive programmingProgramming languageInductive programming

Abstract

fetched live from OpenAlex

AGERE! 2013 was the third iteration of AGERE! held alongside SPLASH. workshop -- which focuses on concerns of modelling, design and programming of systems, where decentralized control is an underlying assumption -- has emerged as a venue that brings together approaches from a family of paradigms variously referred to as Actors, active objects, agents, etc. Actors and more broadly object-oriented concurrent programming -- which couple object-oriented programming with concurrency -- offer a clean and powerful model for computation, which is gaining in popularity with adoption in mainstream languages, frameworks and libraries. Agents and agent-oriented programming provide a further layer of abstraction on top of actors and objects, conceiving concurrent/distributed systems as organizations of autonomous task-oriented entities featuring proactive and reactive behaviors, and interacting in a shared environment. The growing interest in libraries and frameworks supporting Actors or Actor-like mechanisms for use in mainstream platforms calls for tackling of both conceptual and practical hurdles that practitioners may face in using them. For example, how do we best integrate active and passive entities or entities based on different models of concurrency? More generally, it calls for tackling all those problems which become important as soon as these approaches start aiming to become the solution of choice for modelling, designing and programming large and complex software systems. Accordingly, AGERE!'s general theme has evolved to address the question of how these models and abstractions can help improve the way we think about about problems, the way we design, implement, test and validate models and systems, and finally, inform the tools we develop to aid these processes. AGERE! 2013 hosted two invited lectures, one by Yoshiki Ohshima from VPRI and another by Ole Lehrmann Madsen. Ohshima's talk -- titled The future of personal computing system -- reporting VPRI's work as part of the the STEP project -- discussed how the complexity of system construction can be tackled by creating meta-languages which allow us to build and experiment with new domain-specific languages. With these new languages, we can describe different parts of systems in a cleaner and more intention-revealing manner. From a conceptual point of view, remain the fundamental building blocks of the approach; however, decentralization of control and asynchronous interactions - alongside synchronous ones - appear to be a part of the foundation as well. Madsen's talk -- titled SIMULA style concurrent objects -- introduced sub-pattern restrictions as a mechanism used for defining safe concurrency abstractions in a new experimental version of Beta. Besides specific mechanisms, Beta -- being the successor of Simula -- has been designed to naturally support the modelling of concurrent activities, where Simula was originally designed to model and simulate activities in the real world.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0050.005
Open science0.0020.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0180.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.291
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

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