دانلود کتاب سی‌وششمین کنفرانس سیستم‌های هوشمند برزیل، BRACIS 2026

The 36th Brazilian Conference on Intelligent Systems (BRACIS 2026) stands as one of the most significant Brazilian events for researchers in 2026, focused on publishing groundbreaking work in Artificial and Computational Intelligence. BRACIS was formed from the merger of Brazil’s two leading scientific events in these fields: the Brazilian Symposium on Artificial Intelligence (SBIA, 21 editions) and the Brazilian Symposium on Neural Networks (SBRN, 12 editions). This year marked the 36th edition of BRACIS, continuing the numbering from the first edition of SBIA, in honor of the history of the Brazilian scientific community. Supported by the Brazilian Computer Society (SBC), together with the Special Committees on Artificial Intelligence (CE-IA) and Computational Intelligence (CE-IC), BRACIS 2026 served as a platform to promote both theoretical advancements and robust practical applications in these IA/IC (Artificial/Computational Intelligence) fields. The conference promoted the exchange of innovative ideas among researchers, practitioners, and industry leaders. In 2026, BRACIS was held in Cuiabá, Mato Grosso, organized by the Universidade Federal do Mato Grosso (UFMT). The conference took place alongside four other events: the National Meeting on Artificial and Computational Intelligence (ENIAC), the Symposium on Information and Human Language Technology (STIL), the Symposium on Knowledge Discovery, Mining and Learning (KDMiLe), and the Workshop- School on Agents, Environments, and Applications (WESAAC). The 15th edition of the CTDIAC (The Brazilian National Contest of Ph.D. and M.Sc. Theses on Artificial and Computational Intelligence) also happened this year. BRACIS 2026 received 582 valid complete paper submissions, each undergoing a rigorous review process conducted by a Program Committee of 493 experienced AI/CI researchers, with the support of 114 additional reviewers, all within a double anonymous format. All papers received at least three reviews from experts in the field. This year, we accepted 40.20% of the submissions, 234 in total, in three key tracks: 135 articles in the main track, showcasing cutting-edge AI/CI methods and solid results; 28 articles in the AI/CI for Social Good track, featuring innovative applications of AI/CI for societal benefit using established methodologies; 65 articles on other AI/CI applications, presenting novel applications using established AI/CI methods, naturally considering the ethical aspects of the application. In addition, 6 top-tier papers published in leading AI conferences and journals were presented during the event. The topics of interest included, but were not limited to, the following: • Agent-Based and Multi-Agent Systems • AI/CI Algorithms and Models • AI and Quantum Computing, Communication, and Technologies • AI Ethics, Accountability, and Societal Impact • AI for Innovation and Technological Sovereignty • Automated, Probabilistic, and Approximate Reasoning • Bioinformatics and Biomedical Engineering Applications of AI • Cognitive Modeling and Human-AI Interaction • Combinatorial and Numerical Optimization • Computer Vision • Constraint Programming and Optimization • Data Mining and Knowledge Discovery • Deep Learning and Neural Networks • Distributed and Decentralized AI • Education for AI and AI for Education • Evolutionary Computation and Metaheuristics • Explainable Artificial Intelligence (XAI) • Federated and Privacy-Preserving Learning • Forecasting and Time Series Analysis • Foundations of Artificial Intelligence and Computational Intelligence • Fuzzy Systems and Soft Computing • Game Playing and Intelligent Interactive Entertainment • Generative AI and Foundation Models • Graph Neural Networks and Relational Learning • Human-Centered AI • Hybrid AI Systems • Information Retrieval, Integration, and Extraction • Intelligent Robotics and Autonomous Vehicles • Knowledge Representation and Reasoning • Large Language Models • Logic-Based Knowledge Representation and Reasoning • Machine Learning • Meta-Learning and Automated Machine Learning (AutoML) • Model-Based Reasoning • Multidisciplinary AI and CI • Natural Language Processing • Ontologies and the Semantic Web • Pattern Recognition and Cluster Analysis • Planning, Routing, and Scheduling • Reinforcement Learning