This volume documents the proceedings of the First International Conference on Biologically Inspired Cognitive Architectures (BICA 2010), which is also the First Annual Meeting of the BICA Society. This conference was preceded by 2008 and 2009 AAAI Fall Symposia on BICA that were similar in content (indeed, the special issue of the International Journal of Machine Consciousness

A.V. Samsonovich (guest editor): International Journal of Machine Consciousness, special issue on Biologically Inspired Cognitive Architectures, Vol. 2, No. 2, 2010.

Like the 2008 and 2009 BICA Symposia, the present BICA 2010 conference contains a wide variety of ideas and approaches, all centered around the theme of understanding how to create general-purpose humanlike artificial intelligence using inspirations from studies of the brain and the mind. BICA is no modest pursuit: the long-term goals are no less than understanding how human and animal brains work, and creating artificial intelligences with comparable or greater functionality. But, in addition to these long-term goals, BICA research is also yielding interesting and practical research results right now.

A cognitive architecture, broadly speaking, is a computational framework for the design of intelligent and even conscious agents. Cognitive architectures may draw their inspiration from many sources, including pure mathematics or physics or abstract theories of cognition. A biologically inspired cognitive architecture (BICA), in particular, is one that incorporates formal mechanisms from computational models of human and animal cognition, drawn from cognitive science or neuroscience. The appeal of the BICA approach should be obvious: currently human and animal brains provide the only physical examples of the level of robustness, flexibility, scalability and consciousness that we want to achieve in artificial intelligence. So it makes sense to learn from them regarding cognitive architectures: both for research aimed at closely replicating human or animal intelligence, and also for research aimed at creating and using human-level artificial intelligence more broadly.

Research on the BICA approach to intelligent agents has focused on several different goals. Some BICA projects have a primary goal of accurately simulating human behavior, either for purely scientific reasons – to understand how the human mind works – or for applications in domains such as entertainment, education, military training, and the like. Others are concerned with even deeper correspondence between models and the human brain, going down to neuronal and sub-neuronal level. The goal in this approach is to understand how the brain works. Yet another approach is concerned with designing artificial systems that are successful, efficient, and robust at performing cognitive tasks that today only humans can perform, tasks that are important for practical applications in the human society and require interaction with humans. Finally, there are BICA projects aimed broadly at creating generally intelligent software systems, without focus on any one application area, but also without a goal of closely simulating human behavior. All four of these goals are represented in the various papers contained in this volume.

The term BICA was coined in 2005 by Defense Advanced Research Projects Agency (DARPA), when it was used as the name of a DARPA program administered by the Information Processing Technology Office (IPTO). The DARPA BICA program was terminated in 2006 (more details are available at the DARPA BICA web page at http://www.darpa.mil/ipto/programs/bica/bica.asp). Our usage of the term “BICA” is similar to its usage in the DARPA program; however, the specific ideas and theoretical paradigms presented in the papers here include many directions not encompassed by DARPA's vision at that time. Moreover, there is no connection between DARPA and the BICA Society.

One of the more notable aspects of the BICA approach is its cross-disciplinary nature. The human mind and brain are not architected based on the disciplinary boundaries of modern science, and to understand them almost surely requires rich integration of ideas from multiple fields including computer science, biology, psychology and mathematics. The papers in this volume reflect this cross-disciplinarity in many ways.

Another notable aspect of BICA is its integrative nature. A well-thought BICA has a certain holistic integrity to it, but also generally contains multiple subsystems, which may in some cases be incorporated into different BICAs, or used in different ways than the subsystem's creator envisioned. Thus, the reader who is developing their own approach to cognitive architectures may find many insights in the papers contained here useful for inspiring their own work or even importing into their own architecture, directly or in modified form.

Finally we would like to call attention to the relationship between cognition, embodiment and development. In our view, to create a BICA with human-level general intelligence, it may not be necessary to engineer all the relevant subsystems in their mature and complete form. Rather, it may be sufficient to understand the mechanisms of cognitive growth in a relatively simple form, and then let the mature forms arise via an adaptive developmental process. In this approach, one key goal of BICA research becomes understanding what the key cognitive subsystems are, how do they develop, and how they become adaptively integrated in a physical or virtual situated agent able to perform tight interactions within its own body, the other entities and the surrounding environment. With this sort of understanding in hand, it might well be possible to create a BICA with human-level general learning capability, and teach it like a child. Potentially, a population of such learners could ignite a cognitive chain reaction of learning from each other and from common resources, such as human instructors or the Internet.

Currently BICA research is still at an early stage, and the practical capabilities of BICA systems are relatively undeveloped. Furthermore, the relationships between the ideas of various researchers in the field are not always clear; and there is considerable knowledge in relevant disciplines that is not yet fully incorporated into our concrete BICA designs. But BICA research is also rapidly developing, with each year bringing significant new insights, moving us closer to our ambitious goals. In this sense, the newborn BICA society, according to the intentions of the Founding Members, will be a main vehicle for the growth and dissemination of breakthrough research in the field of BICA systems. The papers presented in this volume form part of this ongoing process, as will the papers in the ongoing BICA conferences to follow.

Alexei V. Samsonovich, Kamilla R. Jóhannsdóttir, Antonio Chella and Ben Goertzel

Editors