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AISS 2025

The 1st International Conference on Artificial Intelligence for Sustainable Society (AISS2025) provides a common platform for exchanging ideas and future collaboration among AI technologies such as generative AI, which are applicable to Sustainable Development (SD) for Energy and Environment.

Email: Dunn@iact.net

AI Computing and Control for SS: Evolutionary Computation; Machine Learning; Knowledge-based Intelligent Systems; Hybrid Learning System; Remote Sensing; Network Computing; Neural Computing; Optimization Algorithms; Soft Computing; Mechatronic Systems and Optimization Algorithms; Cloud Computing and Big Data; Quantum Computing; Ubiquitous Computing; Signal and Image Processing; Genetic Algorithms; Decision Support Systems; Deep Learning; Autonomous Systems; Network Intelligence and Control; Hybrid Intelligent Systems; Neural Networks; Fuzzy Control.

Welcome to the official website of the 2025 11th International Conference on Robotics and Artificial Intelligence (ICRAI 2025), which will be held in Nagoya, Japan during December 19-21, 2025. The organizing committees for 2025 11th International Conference on Robotics and Artificial Intelligence (ICRAI 2025) will commit for facilitating the interactions among members in the field of robotics and artificial intelligence. Through this conference, the committees intends to enhance the sharing of individual experience and expertise in robotic developments involving a range of AI concepts with particular emphasis on technical challenges associated with varied applications such as humanoid, mobile and other classes of robots.

Email: adam@asr.org

Aerial and Underwater Robotics; Bio-inspired Robotics; Cable Robots, Cognitive Robotics; Cognitive Approach for Robotics; Collaborative Robotics; Collective and Social Robots; Control and Supervision Systems; Human-Robots Interfaces; Humanoid Robots; Humanoids; Intelligent Robotics and Systems; Legged Robots and Manipulation; Mechatronics Systems; MEMS; Micro-robots and Nano-robots; Mobile Robots and Intelligent Autonomous Systems; Modeling and Identification.