W-learning: Competition among Sellsh Q-learners

@inproceedings{Humphrys1995WlearningCA,
  title={W-learning: Competition among Sellsh Q-learners},
  author={Mark Humphrys},
  year={1995}
}
W-learning is a self-organising action-selection scheme for systems with multiple parallel goals, such as autonomous mobile robots. It uses ideas drawn from the subsumption architecture for mobile robots (Brooks), implementing them with the Q-learning algorithm from reinforcement learning (Watkins). Brooks explores the idea of multiple sensing-and-acting agents within a single robot, more than one of which is capable of controlling the robot on its own if allowed. I introduce a model where the… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 24 references

The Society of Mind

Minsky
The Society of Mind • 1986
View 4 Excerpts
Highly Influenced

Coherent Behavior from Many Adaptive Processes

Brooks, Rodney A Brooks
Proceedings of the Third International Conference on Simulation of Adaptive Behavior (SAB-94 • 1994

Proceedings of the Second International Conference on Simulation of Adaptive Behavior

Harvey
Proceedings of the Second International Conference on Simulation of Adaptive Behavior • 1993

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