1064-5462
Published by: Massachusetts Institute of Technology Press
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 655 | 34 | 47 | 8 |
| Engineering and Technology | 1259 | 7 | 9 | 5 |
The topics of Artificial intelligence, Artificial life, Robot, Theoretical computer science and Cognitive science are the focal point of discussions in Artificial Life. Most of the works presented in it deals with Artificial intelligence but it intersects with the subject of Machine learning. It links adjacent topics like Artificial life with Living systems.
Artificial Life facilitates discussions on Robot that incorporate concepts from other fields like Task (project management), Simulation and Human–computer interaction. Discussions in Artificial Life are anchored in the subject of Theoretical computer science and the similar topic of Cellular automaton. The work on Cognitive science addressed in the journal expands to the thematically related Cognition.
The journal papers generally zeroe in on subjects such as Artificial intelligence, Artificial life, Robot, Cognitive science and Theoretical computer science. The most cited papers with studies in Artificial intelligence featured incorporate elements of Genetic algorithm and Human–computer interaction. The study of Artificial life in the published papers encompasses disciplines such as Epistemology, as well as fields such as Field (Bourdieu), all of which overlap with one another.
Artificial intelligence, Evolutionary algorithm, Theoretical computer science, Cellular automaton and Cognitive science are among the topics commonly tackled in the journal. The featured works in Evolutionary robotics, which all belong in the domain if Artificial intelligence, also overlaps with concepts under Scale (chemistry). The work on Evolutionary algorithm tackled in the journal brings together disciplines like Limit cycle, Complexification and Convergence (relationship).
Topics in Theoretical computer science were tackled in line with various other fields like Tournament selection, Set (abstract data type), Class (set theory), Vector space and Autopoiesis. Artificial Life focuses on Cellular automaton but the discussions also offer insight into other areas such as Phenome, Natural selection, Analogy and Multicellular organism. In addition to Cognitive science research, the journal aims to explore topics under Action (philosophy), Stability (learning theory), Categorization and Self.
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 (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 (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, 11.76% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 13.33% were posted by at least one author from the top 10 institutions publishing in the journal. Another 13.33% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 6.67% of all publications and 66.67% 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.
Beyond understanding the research landscape in the field of Artificial Life, it is also essential to understand the career opportunities and progression paths available for individuals who aspire to contribute to this continuously evolving field. Studying artificial life and similar subjects can open up various career avenues beyond academia, including software development, data science, robotics engineering, and more.
Many researchers also branch out into the field of education, utilizing their knowledge and passion for subjects like artificial intelligence and cognitive science to inspire the future generation of inventors, scientists, and innovators. Teaching positions can be quite rewarding and influential, such as a preschool teacher who stimulates curiosity in young minds. If the idea of teaching alongside research in the field of artificial life piques your interest, it's worth learning about the requirements and steps needed to become an education professional.
For instance, in certain regions or states, specific qualifications or credentials are required. If you're keen on finding out more about becoming an educator, you can explore this comprehensive guide on how to become a preschool teacher in Alabama. Whether you're aiming for a teaching role in higher education or looking to impact learners at the beginning of their educational journey, it's necessary to understand the prerequisites and pathways associated with the profession.
In conclusion, a career in artificial life research doesn't necessarily confine you to just research or teaching. It fosters versatility and opens up a myriad of career possibilities that allow you to apply and share your knowledge and findings in innovations that shape our future.
Joel Lehman;Jeff Clune;Dusan Misevic;Christoph Adami
(2020)Silvana S. S. Cardoso;Julyan H. E. Cartwright;Jitka Cejková;Leroy Cronin
(2020)Carlos Gershenson;Carlos Gershenson;Vito Trianni;Justin Werfel;Hiroki Sayama;Hiroki Sayama
(2020)Thomas Helmuth;Lee Spector;Lee Spector;Lee Spector
(2021)Randall D. Beer
(2020)Emily L. Dolson;Alexander Lalejini;Steven Jorgensen;Charles Ofria
(2020)Frank Veenstra;Pablo González de Prado Salas;Kasper Støy;Josh C. Bongard
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Ultimately, choosing the best degree to get aligns with your career goals and personal circumstances. Computer Science remains one of the top majors with diverse pathways, providing both solid earning potential and opportunities for innovation in the tech landscape.
