Discovering Multimodal Behavior in Ms. Pac-Man Through Evolution of Modular Neural Networks

@article{Schrum2016DiscoveringMB,
  title={Discovering Multimodal Behavior in Ms. Pac-Man Through Evolution of Modular Neural Networks},
  author={Jacob Schrum and Risto Miikkulainen},
  journal={IEEE Transactions on Computational Intelligence and AI in Games},
  year={2016},
  volume={8},
  pages={67-81}
}
Ms. Pac-Man is a challenging video game in which multiple modes of behavior are required: Ms. Pac-Man must escape ghosts when they are threats and catch them when they are edible, in addition to eating all pills in each level. Past approaches to learning behavior in Ms. Pac-Man have treated the game as a single task to be learned using monolithic policy representations. In contrast, this paper uses a framework called Modular Multiobjective NEAT (MM-NEAT) to evolve modular neural networks. Each… CONTINUE READING
Highly Cited
This paper has 29 citations. REVIEW CITATIONS
13 Citations
58 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 13 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 58 references

Similar Papers

Loading similar papers…