COAX
发表于 2025-3-21 16:05:43
书目名称Inductive Logic Programming影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0463888<br><br> <br><br>书目名称Inductive Logic Programming影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0463888<br><br> <br><br>书目名称Inductive Logic Programming网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0463888<br><br> <br><br>书目名称Inductive Logic Programming网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0463888<br><br> <br><br>书目名称Inductive Logic Programming被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0463888<br><br> <br><br>书目名称Inductive Logic Programming被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0463888<br><br> <br><br>书目名称Inductive Logic Programming年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0463888<br><br> <br><br>书目名称Inductive Logic Programming年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0463888<br><br> <br><br>书目名称Inductive Logic Programming读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0463888<br><br> <br><br>书目名称Inductive Logic Programming读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0463888<br><br> <br><br>
古老
发表于 2025-3-21 23:21:26
Rapid Restart Hill Climbing for Learning Description Logic Concepts,r expansion by traversing the search tree in a hill climbing manner and rapidly restarts with one-step backtracking after each expansion. We provide an implementation of RRHC in the DL-Learner framework and compare its performance with CELOE using standard benchmarks.
炸坏
发表于 2025-3-22 03:57:36
http://reply.papertrans.cn/47/4639/463888/463888_3.png
表被动
发表于 2025-3-22 05:59:09
Towards Meta-interpretive Learning of Programming Language Semantics, scenario, including abstracting over function symbols, nonterminating examples, and learning non-observed predicates, and propose extensions to Metagol helpful for overcoming these challenges, which may prove useful in other domains.
牵索
发表于 2025-3-22 09:09:11
Towards an ILP Application in Machine Ethics,on approach relies on the non-monotonic features of Answer Set Programming (ASP) and applies ILP. The approach is illustrated by means of examples taken from the preliminary tests conducted with a couple of state-of-the-art ILP algorithms for learning ASP rules.
NAVEN
发表于 2025-3-22 15:06:43
http://reply.papertrans.cn/47/4639/463888/463888_6.png
宿醉
发表于 2025-3-22 17:07:23
Learning Logic Programs from Noisy State Transition Data,sed to understand the underlying model. In this paper, we propose a Differentiable Learning from Interpretation Transition (.-LFIT) algorithm, that can simultaneously output logic programs fully explaining the state transitions, and also learn from data containing noise and error.
Density
发表于 2025-3-22 22:33:47
http://reply.papertrans.cn/47/4639/463888/463888_8.png
使厌恶
发表于 2025-3-23 03:12:11
0302-9743 xamples, background knowledge and hypotheses. Due to its strong representation formalism, based on first-order logic, ILP provides an excellent means for multi-relational learning and data mining, and more generally for learning from structured data..978-3-030-49209-0978-3-030-49210-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
内向者
发表于 2025-3-23 08:00:41
http://reply.papertrans.cn/47/4639/463888/463888_10.png