Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Pattern-oriented software architecture: a system of patterns
Pattern-oriented software architecture: a system of patterns
Software architecture in practice
Software architecture in practice
Toward a Common Component Architecture for High-Performance Scientific Computing
HPDC '99 Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing
Dynamically Reconfigurable Embedded Software - Does It Make Sense?
ICECCS '96 Proceedings of the 2nd IEEE International Conference on Engineering of Complex Computer Systems
Real-Time System Design and Analysis
Real-Time System Design and Analysis
A biologically motivated system for unconstrained online learning of visual objects
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Rapid online learning of objects in a biologically motivated recognition architecture
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Creating Brain-Like Intelligence
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
A dynamic attention system that reorients to unexpected motion in real-world traffic environments
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Combining auditory preprocessing and Bayesian estimation for robust formant tracking
IEEE Transactions on Audio, Speech, and Language Processing
A language for formal design of embedded intelligence research systems
Robotics and Autonomous Systems
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In this paper, we describe the principles and the methodologies that we have researched for the creation of a software infrastructure for bridging the gap from brain-like systems design to standard software technology. Looking at the brain, we constantly take inspiration and choose the relevant principles that our computer-base model should/could be based on. This ranges from the evolution of the brain (phylogenetically and ontogenetically), the inherent autonomy of the currently identified areas, the intrinsic synchronization through the most basic control mechanisms that regulates interaction, communication, and modulation. With these principles in mind, we started to make a subdivision of our system into instance, functional and computing architecture, modeling each sub-system with processes and tools in order to create a basic infrastructure that supports the research and creation of intelligent systems. The basic elements of our infrastructure are the BBCM (Brain Bytes Component Model) and BBDM (Brain Bytes Data Model), created to enable the modularization and reuse of our systems. Based on those, we have developed DTBOS (Design Tool for Brain Operating System), the design environment for supporting graphical design, RTBOS (Real-Time Brain Operating System), the middleware that supports real-time execution of our modular systems, and CMBOS (Control-Monitor Brain Operating System) to enable the monitoring of running modules. We will show the feasibility of the established environment by shortly describing some of the experimental systems in the area of cognitive robotics that we have created. This will serve to give a more concrete understanding of the dimensions and the type of systems that we have been able to create.