2015 - Volume 03

Tarek R. Besold & Kai-Uwe Kühnberger (eds.)
Proceedings of the Workshop on "Neural-Cognitive Integration" (NCI @ KI 2015)

Workshop Proceedings
Artificial Intelligence

A seamless coupling between learning and reasoning is commonly taken as basis for
intelligence in humans and, in close analogy, also for the biologically-inspired (re-)creation
of human-level intelligence with computational means. Still, one of the unsolved
methodological core issues in AI, cognitive systems modelling, and cognitive neuroscience
is the question of the integration between connectionist sub-symbolic (i.e., neural-level)
and logic-based symbolic (i.e., cognitive-level) approaches to representation, computation,
(mostly sub-symbolic) learning, and (mostly symbolic) reasoning.

Researchers therefore have for years been interested in the relation between subsymbolic/
neural and symbolic/cognitive modes of representation and computation: The
brain has a neural structure which operates on the basis of low-level processing of
perceptual signals, but cognition also exhibits the capability to perform high-level
reasoning and symbol processing. Against this background, symbolic/cognitive
interpretations of ANN architectures seem desirable as possible sources of an additional
(bridging) level of explanation of cognitive phenomena of the human brain (assuming that
suitably chosen ANN models correspond in a meaningful way to their biological

Furthermore, so called neural-symbolic representations and computations promise the
integration of several complementary properties: the interpretability, the possibilities of
direct control, coding, and knowledge extraction offered by symbolic/cognitive paradigms,
together with the higher degree of biological motivation, the learning capacities, robust
fault-tolerant processing, and generalization capabilities to similar input known from subsymbolic/
neural models.

Recent years have seen new developments in the modelling and analysis of artificial
neural networks (ANNs) and in formal methods for investigating the properties of general
forms of representation and computation. As result, new and more adequate tools for
relating the sub-symbolic/neural and the symbolic/cognitive levels of representation,
computation, and (consequently) explanation seem to have become available, allowing to
gain new perspectives on and insights into the interplay and possibilities of cross-level
bridging and integration between paradigms.

Also, more theoretical and conceptual work in cognitive science and philosophy of mind
and cognition has found its way into AI as exemplified, for instance, by the growing
number of projects following an “embodied approach” to AI, in doing so hoping to solve or
avoid, among others, the current mismatch between neural and symbolic perspectives on
cognition and intelligence.

The aim of this interdisciplinary workshop therefore is to bring together recent work
addressing questions related to open issues in neural-cognitive integration, i.e., research
trying to bridge the gap(s) between different levels of description, explanation,
representation, and computation in symbolic and sub-symbolic paradigms, and which
sheds light onto canonical solutions or principled approaches occurring in the context of
neural-cognitive integration.

September, 2015

Tarek R. Besold
Kai-Uwe Kühnberger


AUTHOR = {Tarek R. Besold and Kai-Uwe K\"uhnberger (eds.)},
editor = {K\"uhnberger, K.-U. and K\"onig, P. and Walter, S.},
TITLE = {Proceedings of the Workshop on \lq \lq Neuarl-Cognitive Integration" (NCI@KI 2015},
PUBLISHER = {Institute of Cognitive Science},
YEAR = {2015},
volume = {03-2015},
series = {Publications of the Institute of Cognitive Science},
address = {Osnabr\"uck},
isbn = {1610-5389},

03_2015.pdf5.16 MB