| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Electronics and Electrical Engineering | 489 | 6 | 15 | 4 |
| Computer Science | 1088 | 5 | 6 | 2 |
The main research concerns discussed in Artificial Life and Robotics are Artificial intelligence, Robot, Control theory, Computer vision and Simulation. Topics in Artificial intelligence were tackled in line with various other fields like Machine learning and Pattern recognition. Artificial Life and Robotics focuses on Robot as well as the interrelated topic of Human–computer interaction.
Control theory, Nonlinear system, Control system and Trajectory are among the areas of Control theory tackled. Artificial Life and Robotics features Computer vision research that overlaps with concepts in Position (vector). The works on Artificial neural network deal in particular with Time delay neural network.
The most cited publications investigate areas of study like Artificial intelligence, Robot, Simulation, Control theory and Human–computer interaction. The works on Artificial intelligence tackled in the most cited articles bring together disciplines like Genetic algorithm, Machine learning and Computer vision. The published papers explore topics in Robot which can be helpful for research in disciplines like Control system, Process (computing) and Key (cryptography).
Artificial Life and Robotics investigates areas of study like Artificial intelligence, Robot, Control theory, Computer vision and Artificial neural network. The studies on Artificial intelligence discussed can also contribute to research in the domains of Machine learning, Task (project management) and Pattern recognition. In particular, the Robot works presented emphasize discussions on Mobile robot.
Control theory research presented in Artificial Life and Robotics encompasses a variety of subjects, including Process (computing), Motion planning and Rotor (electric). The concepts on Artificial neural network presented in the journal can also apply to other research fields, including Gait, Waveform, Computer hardware and Integrated circuit. Some problems in Human–computer interaction that were presented in Artificial Life and Robotics overlapped with concepts under Camouflage, Robotics and Information system.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Artificial Life and Robotics (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Artificial Life and Robotics (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 16.42% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 30.36% were posted by at least one author from the top 10 institutions publishing in the journal. Another 14.29% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 33.93% of all publications and 21.43% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Xixun Wang;Yoshiki Mizukami;Makoto Tada;Fumitoshi Matsuno
(2021)Xixun Wang;Kozo Moriyama;Lucas Brooks;Shin Kameyama
(2021)Ryo Ariizumi;Kentaro Koshio;Motoyasu Tanaka;Fumitoshi Matsuno
(2020)Sebastian Herzog;Florentin Wörgötter
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