TY - JOUR
T1 - Linking neural and symbolic representation and processing of conceptual structures
AU - van der Velde, Frank
AU - Forth, Jamie
AU - Nazareth, Deniece S.
AU - Wiggins, Geraint A.
PY - 2017/8/10
Y1 - 2017/8/10
N2 - We compare and discuss representations in two cognitive architectures aimed at representing and processing complex conceptual (sentence-like) structures. First is the Neural Blackboard Architecture (NBA), which aims to account for representation and processing of complex and combinatorial conceptual structures in the brain. Second is IDyOT (Information Dynamics of Thinking), which derives sentence-like structures by learning statistical sequential regularities over a suitable corpus. Although IDyOT is designed at a level more abstract than the neural, so it is a model of cognitive function, rather than neural processing, there are strong similarities between the composite structures developed in IDyOT and the NBA. We hypothesize that these similarities form the basis of a combined architecture in which the individual strengths of each architecture are integrated. We outline and discuss the characteristics of this combined architecture, emphasizing the representation and processing of conceptual structures.
AB - We compare and discuss representations in two cognitive architectures aimed at representing and processing complex conceptual (sentence-like) structures. First is the Neural Blackboard Architecture (NBA), which aims to account for representation and processing of complex and combinatorial conceptual structures in the brain. Second is IDyOT (Information Dynamics of Thinking), which derives sentence-like structures by learning statistical sequential regularities over a suitable corpus. Although IDyOT is designed at a level more abstract than the neural, so it is a model of cognitive function, rather than neural processing, there are strong similarities between the composite structures developed in IDyOT and the NBA. We hypothesize that these similarities form the basis of a combined architecture in which the individual strengths of each architecture are integrated. We outline and discuss the characteristics of this combined architecture, emphasizing the representation and processing of conceptual structures.
KW - Cognitive architecture
KW - Compositional learning
KW - Hebbian learning
KW - In situ representations
KW - Incremental learning
KW - Memory representation
UR - http://www.scopus.com/inward/record.url?scp=85027523273&partnerID=8YFLogxK
U2 - 10.3389/fpsyg.2017.01297
DO - 10.3389/fpsyg.2017.01297
M3 - Article
AN - SCOPUS:85027523273
SN - 1664-1078
VL - 8
JO - Frontiers in psychology
JF - Frontiers in psychology
M1 - 1297
ER -