Task Force on Towards Human-like Intelligence

Task Force Chair

Jacek Mańdziuk
Faculty of Mathematics and Information Science, Warsaw University of Technology
Plac Politechniki 1, 00-661, Warsaw, Poland
e-mail: mandziuk at mini.pw.edu.pl
https://pages.mini.pw.edu.pl/~mandziukj

Task Force Vice-Chair

Włodzisław Duch
Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University
ul. Grudziądzka 5, 87-100 Toruń, Poland
e-mail: wduch at is.umk.pl
http://www.is.umk.pl/~duch

Task Force Vice-Chair

Ah-Hwee Tan
School of Computer Engineering, Nanyang Technological University
Nanyang Avenue, Singapore, Singapore
e-mail: asahtan at ntu.edu.sg
http://www.ntu.edu.sg/home/asahtan/

TF Goals and Scope

In many research domains the existing state-of-the-art AI/CI 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 task force is to promote research activities related to all facets of human-like intelligence. Since the scope of TF comes across several CI/AI fields the TF should facilitate interdisciplinary collaboration of researchers gathered around particular issues.

This interdisciplinary TF combines the ideas from various Computational Intelligence domains including neural networks, genetic/memetic computing, fuzzy logic, reinforcement learning as well as "traditional" Artificial Intelligence techniques related to knowledge representation and acquisition, heuristic search methods and cognitive architectures. The scope of this task force includes, among others, the following topics:

• problem solving based on intuition, creativity, insight, curiosity and imagination;
• autonomous behavior, motivation, knowledge discovery, and guiding role of emotions in discovery;
• lifelong learning, transfer learning, meta-learning, multitasking and learning from partial observations;
• neuro-symbolic approaches to problem solving, combining AI and CI techniques for problem solving;
• brain-inspired cognitive architectures, artificial brains and cognitive robotics;
• neurocognitive informatics, brain-inspired approaches to language;
• cognitive neurodynamics and machine consciousness.