Dergiler / Artificial Intelligence Theory and Applications
Artificial Intelligence Theory and Applications
Artificial Intelligence Theory and Applications (AITA) provides coverage of the most significant work on principles of artificial intelligence, broadly interpreted. The scope of research we cover encompasses contributions of lasting value to any area of artificial intelligence. To be accepted, a paper must be judged to be truly outstanding in its field. AITA is interested in work in core artificial intelligence and at the boundaries, both the boundaries of sub-disciplines of artificial intelligence and the boundaries between artificial intelligence and other fields. ANNOUNCEMENT: We are excited to announce a significant milestone in our journal's journey to further enhance its visibility and recognition within the academic community. Our journal has recently submitted an application for inclusion in the TRDizin Index.
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Amaç
Amaç ve Kapsam The best indicator of the scope of the journal is provided by the areas covered by its Editorial Board in theoretical (artificial intelligence and computing methodologies) and practical (artificial intelligence applications and applied computing) ways. These areas change from time to time, as the field evolves. Artificial Intelligence Artificial intelligence (AI) is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals, which involves consciousness and emotionality. The distinction between the former and the latter categories is often revealed by the acronym chosen. "Strong AI" is usually labelled as artificial general intelligence (AGI) while attempts to emulate 'natural' intelligence have been called artificial biological intelligence (ABI). Leading AI textbooks define the field as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term "artificial intelligence" is often used to describe machines that mimic "cognitive" functions that humans associate with the human mind, such as "learning" and "problem solving". - Automated planning and scheduling - Computer vision - Control methods - Distributed artificial intelligence - Knowledge representation and reasoning - Natural language processing - Search methodologies - Theoretical Foundations of AI Computing Methodologies Soft computing is a collection of methodologies, which aim to exploit tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost. The focus is to publish the highest quality research in application and convergence of the areas of fuzzy logic, neural networks, evolutionary computing, rough sets and other similar techniques to address real world complexities. - Human-centered computing - Information systems - Machine learning - Modeling and simulation - Security and privacy - Symbolic manipulation - Theory of computation - Other computing methodologies (concurrent, distributed, parallel, etc.) AI Applications and Applied Computing Artificial intelligence, defined as intelligence exhibited by machines, has many applications in today's society. More specifically, it is "Weak AI", the form of AI where programs are developed to perform specific tasks, that is being utilized for a wide range of activities including medical diagnosis, electronic trading platforms, robot control, and remote sensing. AI has been used to develop and advance numerous fields and industries, including finance, healthcare, education, transportation, and more. AI researchers have created many tools to solve the most difficult problems in computer science. - Arts and humanities - Computer forensics - Computing technologies - Computing/technology policy - Document management and text processing - Education - Electronic commerce - Enterprise computing - Law, social and behavioral sciences -Life and medical sciences - Operations research - Physical sciences and engineering Yayımlanma Ayları Mayıs Ekim