ICSE '94 Proceedings of the 16th international conference on Software engineering
On the criteria to be used in decomposing systems into modules
Communications of the ACM
Biorobotics
The Neural Simulation Language: A System for Brain Modeling
The Neural Simulation Language: A System for Brain Modeling
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Whiskerbot: A Robotic Active Touch System Modeled on the Rat Whisker Sensory System
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
IEEE Transactions on Neural Networks
SCRATCHbot: active tactile sensing in a whiskered mobile robot
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
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Biological computational modellers are becoming increasingly interested in building large, eclectic models, including components on many different computational substrates, both biological and non-biological. At the same time, the rise of the philosophy of embodied modelling is generating a need to deploy biological models as controllers for robots in real-world environments. Finally, robotics engineers are beginning to find value in seconding biomimetic control strategies for use on practical robots. Together with the ubiquitous desire to make good on past software development effort, these trends are throwing up new challenges of intellectual and technological integration (for example across scales, across disciplines, and even across time) - challenges that are unmet by existing software frameworks. Here, we outline these challenges in detail, and go on to describe a newly developed software framework, BRAHMS, that meets them. BRAHMS is a tool for integrating computational process modules into a viable, computable system; its generality and flexibility facilitate integration across barriers, such as those described above, in a coherent and effective way. We go on to describe several cases where BRAHMS has been successfully deployed in practical situations. We also show excellent performance in comparison with a monolithic development approach. Additional benefits of developing in the framework include source code self-documentation, automatic coarse-grained parallelisation, cross-language integration, data logging, performance monitoring, and will include dynamic load-balancing and 'pause and continue' execution. BRAHMS is built on the nascent, and similarly general purpose, model markup language, SystemML. This will, in future, also facilitate repeatability and accountability (same answers ten years from now), transparent automatic software distribution, and interfacing with other SystemML tools.