Titlebook: Artificial General Intelligence; 11th International C Matthew Iklé,Arthur Franz,Ben Goertzel Conference proceedings 2018 Springer Nature Sw

要旨

書目名稱Artificial General Intelligence影響因子(影響力)




書目名稱Artificial General Intelligence影響因子(影響力)學(xué)科排名




書目名稱Artificial General Intelligence網(wǎng)絡(luò)公開度




書目名稱Artificial General Intelligence網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Artificial General Intelligence被引頻次




書目名稱Artificial General Intelligence被引頻次學(xué)科排名




書目名稱Artificial General Intelligence年度引用




書目名稱Artificial General Intelligence年度引用學(xué)科排名




書目名稱Artificial General Intelligence讀者反饋




書目名稱Artificial General Intelligence讀者反饋學(xué)科排名

endoscopy

Resource-Constrained Social Evidence Based Cognitive Model for Empathy-Driven Artificial Intelligenplain, predict and manage behavioral patterns in multi-agent communities. For this purpose, we propose implementation of resource-constrained social evidence based model and discuss possible implications of its application.

arthrodesis

Unsupervised Language Learning in OpenCog,explore how far we can advance grammar learning. We present the current approach employed in the open source OpenCog Artificial Intelligence Platform, describe the cognitive pipeline being constructed and present some intermediate results.

不透明性

憤慨一下

Brandon Kar Meng Choo,Mohd. Farooq Shaikhse Request Confirmation Networks (ReCoNs). ReCoNs are spreading activation networks with units that contain an activation and a state, and are connected by typed directed links that indicate partonomic relations and spatial or temporal succession. By passing activation along the links, ReCoNs can pe

浸軟

scotoma

Brennan J. Sullivan,Shilpa D. Kadammple virtual and physical robots. As such, several main features of a general AM concept were reproduced. Using the strength of temporal coding at the single spike resolution level, this study approaches the AM phenomenon with basic examples in the visual modality. Specifically, the AM include varyi

guardianship

山崩

Preeti Vyas,Rajkumar Tulsawani,Divya Vohoraally Beta distributions, is introduced. An estimate to predict the second order probability of new data, obtained by averaging the second order distributions of partial operators, is derived. The problem of managing the partiality of the operators is presented. A simplistic solution based on estimat

手勢

Brennan J. Sullivan,Shilpa D. Kadamrrently predominant data-driven approasches in AI seem to be lacking humans’ unique ability to solve wide ranges of problems. This situation begs the question of the existence of principles that underlie general problem-solving capabilities. We approach this question through the mathematical formula