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Shape Formation by Programmable Particles Brief Announcement DISC 2017 Giuseppe Antonio Di Luna, Paola Flocchini, Nicola Santoro, Giovanni Viglietta, Yukiko Yamauchi Vienna October 19, 2017 Shape Formation by Programmable Particles


  1. Shape Formation by Programmable Particles Brief Announcement – DISC 2017 Giuseppe Antonio Di Luna, Paola Flocchini, Nicola Santoro, Giovanni Viglietta, Yukiko Yamauchi Vienna – October 19, 2017 Shape Formation by Programmable Particles

  2. Amoebots /In this model, particles occupy nodes of a hexagonal grid./ Shape Formation by Programmable Particles

  3. Amoebots /A particle can move by expanding and contracting ./ Shape Formation by Programmable Particles

  4. Amoebots /A particle can move by expanding and contracting ./ Shape Formation by Programmable Particles

  5. Amoebots /A particle can move by expanding and contracting ./ Shape Formation by Programmable Particles

  6. Amoebots /A particle can move by expanding and contracting ./ Shape Formation by Programmable Particles

  7. Amoebots /A particle can move by expanding and contracting ./ Shape Formation by Programmable Particles

  8. Amoebots /A system of particles is given./ Shape Formation by Programmable Particles

  9. Amoebots /Particles move asynchronously ./ Shape Formation by Programmable Particles

  10. Amoebots /Particles move asynchronously ./ Shape Formation by Programmable Particles

  11. Amoebots /At each step, any set of particles is activated by an adversary ./ Shape Formation by Programmable Particles

  12. Amoebots /At each step, any set of particles is activated by an adversary ./ Shape Formation by Programmable Particles

  13. Shape Formation final shape /The goal is to form a shape that is given as input to all particles./ Shape Formation by Programmable Particles

  14. Shape Formation initial configuration final configuration deterministic algorithm /The shape formation algorithm should be deterministic ./ Shape Formation by Programmable Particles

  15. Shape Formation final configuration initial configuration deterministic algorithm /The shape can be scaled up depending on the size of the system./ Shape Formation by Programmable Particles

  16. Related Literature Original Amoebot paper: Z. Derakhshandeh, R. Gmyr, T. Strothmann, R.A. Bazzi, A.W. Richa, and C. Scheideler Leader election and shape formation with self-organizing programmable matter In Proceedings of 21st International Conference on DNA Computing and Molecular Programming (DNA) , 117–132, 2015 Randomized shape-formation algorithm for sequentially activated Amoebots starting from a triangular shape: Z. Derakhshandeh, R. Gmyr, A.W. Richa, C. Scheideler, and T. Strothmann Universal shape formation for programmable matter In Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA) , 289–299, 2016 Shape Formation by Programmable Particles

  17. Our Particle Model The n particles in the system: initially form any simply connected shape know the final shape but do not know n have a constant amount of internal memory are anonymous and start in the same state can only see and communicate with adjacent particles do not have a compass may not agree on a clockwise direction are activated asynchronously execute the same deterministic algorithm cannot occupy the same node Shape Formation by Programmable Particles

  18. Unbreakable Symmetry /If the system has a center of symmetry not in a grid node.../ Shape Formation by Programmable Particles

  19. Unbreakable Symmetry /Then this symmetry is impossible to break./ Shape Formation by Programmable Particles

  20. Unbreakable Symmetry /The same holds for systems with a 3-fold rotational symmetry./ Shape Formation by Programmable Particles

  21. Unbreakable Symmetry /If the center is not in a grid node, the symmetry is unbreakable./ Shape Formation by Programmable Particles

  22. Statement of Results Theorem If the system initially has an unbreakable symmetry, it cannot form shapes that do not have the same symmetry. Theorem For all other cases, there is a universal shape-formation algorithm, provided that the system is sufficiently large. The particles perform O ( n 2 ) moves in total and terminate in O ( n 2 ) rounds. Shape Formation by Programmable Particles

  23. Universal Shape-Formation Algorithm /Start with a sufficiently large simply connected system./ Shape Formation by Programmable Particles

  24. Universal Shape-Formation Algorithm / Phase 1: attempt to elect a leader./ Shape Formation by Programmable Particles

  25. Universal Shape-Formation Algorithm / Phase 2: construct a spanning forest./ Shape Formation by Programmable Particles

  26. Universal Shape-Formation Algorithm / Phase 3: agree on a clockwise direction./ Shape Formation by Programmable Particles

  27. Universal Shape-Formation Algorithm / Phase 4: form one line per leader./ Shape Formation by Programmable Particles

  28. Universal Shape-Formation Algorithm / Phase 5: determine the scale of the final shape and assign roles./ Shape Formation by Programmable Particles

  29. Universal Shape-Formation Algorithm / Phase 6: form the final shape./ Shape Formation by Programmable Particles

  30. Universal Shape-Formation Algorithm / Phase 6: form the final shape./ Shape Formation by Programmable Particles

  31. Matching Lower Bound /This example shows that O ( n 2 ) total moves are optimal./ Shape Formation by Programmable Particles

  32. Matching Lower Bound / Open problem: are O ( n 2 ) rounds optimal?/ Shape Formation by Programmable Particles

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