A novel agent-based simulation framework for sensing in complex adaptive environments

2017-08-19 · Muaz A. Niazi, Amir Hussain

In this paper we present a novel Formal Agent-Based Simulation framework (FABS). FABS uses formal specification as a means of clear description of wireless sensor networks (WSN) sensing a Complex Adaptive Environment. This specification model is then used to develop an agent-based model of both the wireless sensor network as well as the environment. As proof of concept, we demonstrate the application of FABS to a boids model of self-organized flocking of animals monitored by a random deployment of proximity sensors.

📄 PDF Abstract BibTeX arXiv:1708.05875

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Traffic Co-Simulation Framework Empowered by Infrastructure Camera Sensing and Reinforcement Learning

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Multi-agent Reinforcement Learning reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)+2

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Bayesian Optimization

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Active Learning

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2018-07-14

We present the novel adaptive hierarchical sensing algorithm K-AHS, which samples sparse or compressible signals with a measurement complexity equal to that of Compressed Sensing (CS). In contrast to CS, K-AHS is adaptiv…

compressed sensing