The challenge of creating a real-life computational equivalent of the human mind requires that we better understand at a computational level how natural intelligent systems develop their cognitive and learning functions.

In recent years, biologically inspired cognitive architectures (BICA) have emerged as a powerful new approach toward gaining this kind of understanding (here “biologically inspired” is understood broadly as “brain-mind inspired”). Still, despite impressive successes and growing interest in BICA, wide gaps separate different approaches from each other and from solutions found in biology, preventing us from solving the challenge.

The narrow focus on the challenge brings together four schools of thought:

(1) computational neuroscience, that tries to understand how the brain works in terms of connectionist models;

(2) cognitive modeling, pursuing higher-level computational description of human cognition;

(3) human-level artificial intelligence, aiming at generally intelligent artifacts that can replace humans at work;

(4) human-like learners: artificial minds that can be understood by humans intuitively, that can learn like humans, from humans and for human needs.

The comparative table created by panelists of the BICA 2009 forum clearly demonstrates that a joined discussion of the four schools is possible and can be highly productive and synergistic (http://members.cox.net/bica2009/cogarch/). The intended spotlight in 2010 is on (4).

Important Dates

• BICA 2009