技能 人工智能 知识表示与推理会议定位分析

知识表示与推理会议定位分析

v20260724
international-conference-on-principles-of-knowledge-representation-and-reasoning
本技能是为提交顶级人工智能会议(特别是知识表示与推理会议)的作者提供的策略指南。它帮助用户评估论文的适用性、定位和证据要求。内容深入指导用户应关注的范围,如形式语义、非单调推理和本体论,确保论文在高度专业的知识表示社区中得到正确的定位。适用于投稿前的策略规划和稿件重塑。
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International Conference on Principles of Knowledge Representation and Reasoning (KR)

Conference positioning

International Conference on Principles of Knowledge Representation and Reasoning (KR) is a top computer-science conference venue for logic, reasoning, ontologies, nonmonotonic reasoning, argumentation, and explainable symbolic AI. It rewards a reasoning paper where representational commitments and formal semantics are central. Treat this skill as a fit / venue-selection / re-framing tool for conference submission strategy, not as a substitute for the current year's CFP, author kit, ethics policy, or submission portal.

Because CS conferences change deadlines, templates, page limits, review workflow, artifact rules, AI-use policy, and rebuttal formats every cycle, always verify the live official instructions before making a submission-ready recommendation. Start from the official source anchor recorded for this venue in ../../resources/conference-roster.md and ../../resources/official-source-map.md.

When to trigger

  • The author names KR / International Conference on Principles of Knowledge Representation and Reasoning as the target venue.
  • A manuscript in logic needs a conference-fit read before being formatted or submitted.
  • The paper must be re-framed from journal style or arXiv style into a selective CS conference narrative.
  • The author needs an evidence-gap, anonymity, artifact, rebuttal, or re-routing diagnosis for this venue.

Scope & topic fit

  • Core fit: logic, reasoning, ontologies, nonmonotonic reasoning, argumentation, and explainable symbolic AI.
  • Best submissions make a precise contribution type visible: algorithm, theorem, system, dataset, benchmark, empirical finding, design artifact, tool, or socio-technical analysis.
  • The paper should explain why the result matters to KR's reviewers, not just why it is interesting to the authors' lab or product context.
  • Position related work against the most recent conference-cycle papers in this venue and its closest siblings; stale comparisons are a common early-review weakness.
  • If the contribution is interdisciplinary, state which part is CS research and which part is domain evidence.

Venue-specific calibration

  • Reviewer lens: Treat KR as a knowledge representation venue whose reviewers expect the scope and evidence to match its own community. Do not submit a generic CS paper until the introduction names the exact subcommunity, contribution type, and proof or empirical standard.
  • Contribution hook to foreground: the venue-specific contribution bar.
  • Scope vocabulary to use naturally in the abstract and introduction: logic, reasoning, ontologies, nonmonotonic reasoning, argumentation, and explainable symbolic AI.
  • Distinctive fingerprint for reviewer calibration: logic, reasoning, ontologies, nonmonotonic, argumentation, explainable, symbolic, venue-specific, contribution, knowledge, representation.
  • Official anchor domain: kr.org. Quote annual rules only after opening that source and the current-year CFP/author kit.

Close-neighbor routing guardrail

  • Route to KR when the paper is about formal knowledge representation, reasoning, logics, ontologies, constraints, argumentation, or planning-relevant representation principles.
  • Compare SAT/CP for satisfiability or constraint solving, ISWC/K-CAP for semantic-web or knowledge-capture systems, and AAAI/IJCAI for broader AI.

What distinguishes this venue from its closest siblings

  • What KR is. The conference on Principles of Knowledge Representation and Reasoning — logics, ontologies, nonmonotonic and epistemic reasoning.
  • vs CP / SAT. CP is constraint solving and SAT is Boolean satisfiability; KR is about representation and reasoning formalisms, not solver engineering.
  • vs AAAI/IJCAI. The generalist AI flagships also take KR work; choose KR when the formal-reasoning community is the primary audience.

KR-specific routing detail

  • Prefer KR when the contribution is about representation and reasoning formalisms: logics, ontologies, argumentation, belief change, nonmonotonic reasoning, constraints, planning knowledge, or explainable reasoning.
  • Route intrusion detection, attacks, defenses, and security measurement to RAID/security venues; route satisfiability-specific solving to SAT and semantic-web deployment to ISWC.
  • KR evidence should make formal semantics, reasoning properties, expressiveness/complexity, examples, and solver or empirical support explicit.

Method & evidence bar

  • Compare against current strong baselines and explain exactly what changes in the algorithm, objective, data, or inference procedure.
  • Report ablations that isolate the claimed mechanism; do not rely on aggregate benchmark wins alone.
  • Document data, compute, hyperparameters, model selection, and failure cases so the result can be reviewed as science rather than demo output.
  • For KR, the evidence must support the venue-specific signature: a reasoning paper where representational commitments and formal semantics are central.
  • Include limitations, negative results, compute/resource reporting, data provenance, and ethics details when they affect the claim.

Structure & house style

  • Frame the contribution as a reusable idea: method, theory, benchmark, dataset, system, or socio-technical finding.
  • Separate main claims from exploratory results; reviewers at top AI venues punish overclaiming and hidden cherry-picking.
  • Use the current official template exactly; do not guess page limits, font sizes, supplement rules, anonymity exceptions, or camera-ready requirements from old cycles.
  • The introduction should answer: problem, why now, what is new, why this venue, and what evidence proves the claim.
  • Put the strongest result in the main paper, not only in the appendix or supplement; reviewers should not have to reconstruct the contribution.

Official-cycle checklist

  • Open the live official venue page: https://kr.org/
  • Re-check the current cycle's CFP, author kit, submission system, abstract/paper deadlines, page limits, supplementary-material rules, anonymity policy, dual-submission policy, ethics policy, AI-use policy, artifact/code/data expectations, rebuttal/author-response format, and camera-ready requirements.
  • Confirm the review workflow and portal: OpenReview / CMT / HotCRP / PCS / START or society portal, as specified for the current cycle.
  • Check whether accepted papers require in-person presentation, separate registration, artifact badges, proceedings copyright, or post-acceptance release forms.
  • If the live official instructions conflict with this skill, the official instructions win.

Pre-submission self-check

  • One sentence states why this manuscript belongs at KR, using the venue's scope rather than generic "top conference" language.
  • The claim is calibrated to the evidence: no broader than the datasets, proofs, systems, user studies, deployments, or threat model support.
  • Related work includes the nearest current-cycle knowledge representation papers and explains the technical delta.
  • The paper satisfies the current official template, anonymity, ethics, artifact, and rebuttal requirements.
  • The main paper is self-contained enough for reviewers to evaluate novelty and correctness without hunting through external links.

Common desk-reject triggers

  • Leaderboard-only novelty with weak explanation of why the method works.
  • Unclear data contamination, missing baselines, or evaluation that cannot be reproduced.
  • Claims about safety, fairness, health, or society without matching evidence and limitations.
  • Formatting, anonymity, dual-submission, external-link, or supplement violations under the current-year policy.
  • A contribution framed for a neighboring field while giving KR reviewers too little technical or empirical substance.

Re-routing decision

If the paper misses KR's bar, compare against neural-information-processing-systems / international-conference-on-machine-learning / international-conference-on-learning-representations / aaai-conference-on-artificial-intelligence. Re-route based on contribution type, not prestige: theory to a theory venue, systems to a systems venue, application-heavy work to a domain venue, and early ideas to workshops or shorter tracks when the official CFP supports them.

Output format

[Fit] High / Medium / Low (one-line reason)
[Target] International Conference on Principles of Knowledge Representation and Reasoning (KR)
[Contribution type] algorithm / theory / system / dataset / benchmark / empirical / design / security / other
[Main evidence gap] <single most important missing proof, experiment, study, artifact, or policy check>
[Official items to re-check] CFP / author kit / deadline / format / anonymity / ethics / AI-use / artifact / rebuttal / camera-ready
[Top rejection risk] <venue-specific risk>
[Re-route suggestion] <better-matched conference or journal if not a fit>
信息
Category 人工智能
Name international-conference-on-principles-of-knowledge-representation-and-reasoning
版本 v20260724
大小 9.24KB
更新时间 2026-07-28
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