SOAR: an architecture for general intelligence
Artificial Intelligence
Tracking and data association
A design for the ICARUS architecture
ACM SIGART Bulletin
Layered control architectures in robots and vertebrates
Adaptive Behavior
Conceptual Spaces: The Geometry of Thought
Conceptual Spaces: The Geometry of Thought
Journal of Cognitive Neuroscience
A Model of Prefrontal Cortical Mechanisms for Goal-directed Behavior
Journal of Cognitive Neuroscience
Reformulation of the theory of conceptual spaces
Information Sciences: an International Journal
Information Sciences: an International Journal
Abducing chances in hybrid humans as decision makers
Information Sciences: an International Journal
Social cooperation and competition in the mixed reality space eXperience Induction Machine XIM
Virtual Reality - Mediated Presence: Virtual Reality, Mixed Environments and Social Networks, Part 1.Guest Editors: Anna Spagnolli; Matthew Lombard; Luciano Gamberini
Learning to talk about events from narrated video in a construction grammar framework
Artificial Intelligence - Special volume on connecting language to the world
On the design of intelligent robotic agents for assembly
Information Sciences: an International Journal
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
A model of computation and representation in the brain
Information Sciences: an International Journal
Information Sciences: an International Journal
A neuromorphic model of spatial lookahead planning
Neural Networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Acquisition of hierarchical reactive skills in a unified cognitive architecture
Cognitive Systems Research
Efficient jitter compensation using double exponential smoothing
Information Sciences: an International Journal
The effect of guided and free navigation on spatial memory in mixed reality
Proceedings of the Virtual Reality International Conference: Laval Virtual
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A wide range of neuroscientific studies suggest the existence of cognitive mechanisms like attention, prediction, anticipation and strong vertical interactions between different hierarchical layers of the brain while performing complex tasks. Despite advances in both cognitive brain research and in the development of brain-inspired artificial cognitive systems, the interplay of these key ingredients of cognition remain largely elusive and unquantified in complex real-world tasks. Furthermore, it has not yet been demonstrated how a self-contained hierarchical cognitive system acting under limited resource constraints can quantifiably benefit from the incorporation of top-down and bottom-up attentional mechanisms. In this context, an open fundamental question is how a data association mechanism can integrate bottom-up sensory information and top-down knowledge. Here, building on the Distributed Adaptive Control (DAC) architecture, we propose a single framework for integrating these different components of cognition and demonstrate the framework's performance in solving real-world and simulated robot tasks. Using the model we quantify the interactions between prediction, anticipation, attention and memory. Our results support the strength of a complete system that incorporates attention, prediction and anticipation mechanisms compared to incomplete systems for real-world and complex tasks. We unveil the relevance of transient memory that underlines the utility of the above mechanisms for intelligent knowledge management in artificial sensorimotor systems. These findings provide concrete predictions for physiological and psychophysical experiments to validate our model in biological cognitive systems.