English

Self-Organized Construction by Minimal Surprise

Robotics 2024-05-07 v1 Multiagent Systems Neural and Evolutionary Computing

Abstract

For the robots to achieve a desired behavior, we can program them directly, train them, or give them an innate driver that makes the robots themselves desire the targeted behavior. With the minimal surprise approach, we implant in our robots the desire to make their world predictable. Here, we apply minimal surprise to collective construction. Simulated robots push blocks in a 2D torus grid world. In two variants of our experiment we either allow for emergent behaviors or predefine the expected environment of the robots. In either way, we evolve robot behaviors that move blocks to structure their environment and make it more predictable. The resulting controllers can be applied in collective construction by robots.

Keywords

Cite

@article{arxiv.2405.02980,
  title  = {Self-Organized Construction by Minimal Surprise},
  author = {Tanja Katharina Kaiser and Heiko Hamann},
  journal= {arXiv preprint arXiv:2405.02980},
  year   = {2024}
}

Comments

Published in 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W)

R2 v1 2026-06-28T16:17:15.902Z