In many research domains the existing state-of-the-art Computational Intelligence / Artificial Intelligence solutions significantly differ from the human competence level. Even though it is generally not clear whether human-like approach would show its upper-hand over existing methods, the exploration of this research path seems to be advantageous and challenging.
The main goal of this symposium is to promote and advance research and technological activities related to all facets of human-like intelligence, both in theory and practice. The organizers encourage submission of the papers describing application of various CI paradigms including deep and shallow neural network learning models, heuristic and evolutionary computing, fuzzy logic, rule based systems, machine learning and statistical methods towards accomplishing human-like intelligent behavior and problem solving.
The CIHLI organizers invite submissions of original previously unpublished innovative research in any topic related to practical and theoretical aspects of human-like intelligent behavior including, but not limited to:
- Models and architectures, including cognitively-plausible architectures and systems for human-like intelligence and humanized computing in theory and practical applications
- Problem solving based on nature, heuristic, intuition, creativity, insight, curiosity and imagination
- Theory and application of deep learning, reinforcement learning, autonomous learning, transfer learning and active learning
- Theory and application of evolutionary, heuristics and bio inspired algorithms, neural networks, fuzzy logic, rule based systems and their hybrid constructions
- Theoretical and practical aspects of future generation computing models and paradigms
- Ambient intelligence and human-like intelligence in image processing, pattern recognition, expert systems, engineering problems, data mining and optimization for industry, finance, transport, logistics, economy, manufacturing, security, games, IoT, VR, healthcare, science, and other domains