Intelligence without representation
Artificial Intelligence
Evolving mobile robots in simulated and real environments
Artificial Life
Evolutionary robotics and the radical envelope-of-noise hypothesis
Adaptive Behavior
Evolutionary neurocontrollers for autonomous mobile robots
Neural Networks - Special issue on neural control and robotics: biology and technology
Grounding and the Entailment Structure in Robots and Artificial Life
Proceedings of the Third European Conference on Advances in Artificial Life
Classification as Sensory-Motor Coordination: A Case Study on Autonomous Agents
Proceedings of the Third European Conference on Advances in Artificial Life
Navigating with an Adaptive Light Compass
Proceedings of the Third European Conference on Advances in Artificial Life
The Dynamical Nightwatch's Problem Solved by the Autonomous Micro-Robot Khepera
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
Learning Subjective "Cognitive Maps" in the Presence of Sensory-Motor Errors
Proceedings of the Third European Conference on Advances in Artificial Life
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The design of behavior generating control structures for real robots acting autonomously in a real and changing environment is a complex task. This is in particular true with respect to the debugging process, the documentation of the encountered behavior, its quantitative analysis and the final evaluation. To successfully implement such a behavior, it is vital to couple the synthesis on a simulator and the experiment on a real robot with a thorough analysis. The available simulator tools in general only allow behavioral snapshots and do not provide the option of online interference. In order to cure these shortcomings, a visualization tool for aposteriori graphical analysis of recorded data sets which gives access to all relevant internal states and parameters of the system is presented. The mini-robot Khepera has been chosen as experimentatory platform.