Exploring the T-Maze: Evolving Learning-Like Robot Behaviors Using CTRNNs

@inproceedings{Blynel2003ExploringTT,
  title={Exploring the T-Maze: Evolving Learning-Like Robot Behaviors Using CTRNNs},
  author={Jesper Blynel and Dario Floreano},
  booktitle={EvoWorkshops},
  year={2003}
}
This paper explores the capabilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement learning-like abilities on a set of T-Maze and double T-Maze navigation tasks, where the robot has to locate and "remember" the position of a reward-zone. The "learning" comes about without modifications of synapse strengths, but simply from internal network dynamics, as proposed by [12]. Neural controllers are evolved in simulation and in the simple case evaluated on a real robot… CONTINUE READING

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