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In this paper we present a novel information-theoretic measure of spa-tiotemporal coordination in a modular robotic system, and use it as a fitness function in evolving the system. This approach exemplifies a new methodology formalizing co-evolution in multi-agent adaptive systems: information-driven evolutionary design. The methodology attempts to link(More)
We present an autoadaptive algorithm for in-use parameter estimation of MEMS inertial accelerometers and gyros 1 using multi-level quasi-static states for greater accuracy and reliability. Multi-level quasi-static states are detected robustly using data from both gyros and accelerometers. Proper estimation of time-varying sensor parameters allows us to(More)
This paper presents a new multi-agent physics-based simulation framework (DISCOVERY), supporting experiments with self-organizing underwater sensor and actuator networks. DISCOVERY models mobile autonomous underwater vehicles, distributed sensor and actuator nodes, as well as multi-agent data-to-decision integration. The simulator is a real-time system(More)
We describe a software system1 to model and visualize 3D or 2D self-assembly of groups of autonomous agents. The system makes a physically accurate estimate of the interaction of agents represented as rigid cubic or tetrahedral structures with variable electrostatic charges on the faces and vertices. Local events cause the agentsý charges to change(More)