Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Intelligence without representation
Artificial Intelligence
Evolving visually guided robots
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Agents that reduce work and information overload
Communications of the ACM
A softbot-based interface to the Internet
Communications of the ACM
Using emergent modularity to develop control systems for mobile robots
Adaptive Behavior - Special issue on environment structure and behavior
Understanding intelligence
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Navigating with an Adaptive Light Compass
Proceedings of the Third European Conference on Advances in Artificial Life
Evolution of homing navigation in a real mobile robot
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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In the context of research on intelligence, autonomous agents and in particular mobile robots are to behave on their own without any human control. Unfortunately, the real world exhibits plenty of noise, uncertainties, sudden changes, etc, which all imposes significant challenges on the design of appropriate control architectures. This chapter starts off with an existing controller, known as the distributed adaptive control architecture and shows how significant improvements can be achieved by incorporating biological mechanisms, such as proprioception. The resulting controller requires much less preprogrammed design knowledge, exhibits more flexible adaptation capabilities, and is more fault tolerant with respect to environmental changes and sensor failures as its predecessors.