Track 4
Track 4: Artificial Intelligence & Cognitive Systems
Track Chairs:
- Sunil Aryal, Deakin University, Australia
Scope
Artificial Intelligence research has produced impressive results in the last few years. Both academia and industry are actively working to advance in the long goal of creating sophisticated machines that can perform tasks usually better executed by humans. The methods to produce intelligent systems have emerged from several subareas, including search methods, intelligent agents, machine learning, knowledge representation, and reasoning, among others. Successful applications include computer vision, social media, medicine, finances, linguistics, robotics, cloud, and edge computing, the Internet of Things (IoT), etc. We hope that this edition of the track Advances in AI can be a forum where researchers from academia and industry may exchange experience, new techniques, and theoretical advances to contribute to the realization of Artificial Intelligence.
Topics
- Machine Learning (Deep Learning, Reinforcement Learning, Statistical Learning, etc.)
- Cognitive Systems / Bio-inspired AI
- Knowledge Representation and Reasoning
- Problem Solving/Search/Planning
- Multi-agent Systems
- Constraint Satisfaction
- Robotics and Perception
- Economic Paradigms and Game Theory
- Human-Robot Interactions
- Self-* Systems (self-configuring, self-healing, self-optimizing, etc.)
- AI and Cloud Computing
- AI and 5G/6G
- AI and Edge Computing
- AI and Social/Crowd Computing
- Data Mining/Social Network Analysis and Mining
- AI Applications in security, sustainability, healthcare, smart cities, medicine, games, logistics, and manufacturing, among others.
PC members:
- Dhiraj Neupane, Changwon National University
- Arbind Agrahari Baniya, Deakin University
- Francesco Piccialli, University of Naples Federico II
- Aditya Ghose, University of Wollongong, Australia
- Ahmed Mohamed Elsayed Omara, University of Ottawa, Canada