Facebook pixel tracking

The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

Contact Info
Website thesai.org
Follow Us
Contact Info
Follow Us

Artificial Intelligence | IJACSA

Artificial intelligence (AI) is the branch of computer science concerned with building systems that perform tasks normally requiring human intelligence, such as reasoning, planning, perception, and language understanding. The field spans symbolic approaches (rule-based expert systems, knowledge graphs, automated planning) and statistical approaches (machine learning, deep neural networks, probabilistic reasoning), increasingly combined to improve interpretability and reliability. AI research addresses search and optimization, multi-agent coordination, knowledge representation, and generalization from limited data. Applications range from recommendation engines and autonomous vehicles to fraud detection, scientific discovery, and decision-support systems in medicine, finance, and manufacturing. Agentic AI, systems that plan and act across multi-step tasks, has become a leading research focus; Stanford's 2026 AI Index Report finds most organizations are still experimenting with AI agents rather than deploying them at scale. As a peer-reviewed, open-access artificial intelligence journal, IJACSA (an AI journal indexed in Scopus) publishes research spanning foundational algorithms to applied AI systems evaluated on real-world datasets.

Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed September 2026

Smart Parking Architecture based on Multi Agent System

Vol. 10, Issue 3 (2019) · 31 citations

Finding a parking space in big cities is becoming more and more impossible. In addition, the emergence of car has created several problems relating to urban mobility for the city. But with the development of technology,…

Towards the Algorithmic Detection of Artistic Style

Vol. 10, Issue 1 (2019)

The artistic style of a painting can be sensed by the average observer, but algorithmically detecting a painting’s style is a difficult problem. We propose a novel method for detecting the artistic style of a painting th…