英文簡介Memetic Computing期刊介紹

Memes have been defined as basic units of transferrable information that reside in the brain and are propagated across populations through the process of imitation. From an algorithmic point of view, memes have come to be regarded as building-blocks of prior knowledge, expressed in arbitrary computational representations (e.g., local search heuristics, fuzzy rules, neural models, etc.), that have been acquired through experience by a human or machine, and can be imitated (i.e., reused) across problems.

The Memetic Computing journal welcomes papers incorporating the aforementioned socio-cultural notion of memes into artificial systems, with particular emphasis on enhancing the efficacy of computational and artificial intelligence techniques for search, optimization, and machine learning through explicit prior knowledge incorporation. The goal of the journal is to thus be an outlet for high quality theoretical and applied research on hybrid, knowledge-driven computational approaches that may be characterized under any of the following categories of memetics:

Type 1: General-purpose algorithms integrated with human-crafted heuristics that capture some form of prior domain knowledge; e.g., traditional memetic algorithms hybridizing evolutionary global search with a problem-specific local search.

Type 2: Algorithms with the ability to automatically select, adapt, and reuse the most appropriate heuristics from a diverse pool of available choices; e.g., learning a mapping between global search operators and multiple local search schemes, given an optimization problem at hand.

Type 3: Algorithms that autonomously learn with experience, adaptively reusing data and/or machine learning models drawn from related problems as prior knowledge in new target tasks of interest; examples include, but are not limited to, transfer learning and optimization, multi-task learning and optimization, or any other multi-X evolutionary learning and optimization methodologies.

期刊簡介Memetic Computing期刊介紹

《Memetic Computing》自2009出版以來，是一本計算機科學優(yōu)秀雜志。致力于發(fā)表原創(chuàng)科學研究結(jié)果，并為計算機科學各個領(lǐng)域的原創(chuàng)研究提供一個展示平臺，以促進計算機科學領(lǐng)域的的進步。該刊鼓勵先進的、清晰的闡述，從廣泛的視角提供當前感興趣的研究主題的新見解，或?qū)彶槎嗄陙砟硞€重要領(lǐng)域的所有重要發(fā)展。該期刊特色在于及時報道計算機科學領(lǐng)域的最新進展和新發(fā)現(xiàn)新突破等。該刊近一年未被列入預警期刊名單，目前已被權(quán)威數(shù)據(jù)庫SCIE收錄，得到了廣泛的認可。

該期刊投稿重要關(guān)注點：

• 預計審稿時間：
• 國際TOP期刊
• 計算機科學
• COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
• SCIE
• 中科院2區(qū)
• 非預警