Book chapter
Chemotaxis-Inspired Cellular Primitives for Self-Organizing Shape Formation
Morphogenetic Engineering, pp 209-237
01 Jan 2012
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Motivated by the ability of living cells to form specific shapes and structures, we are investigating chemotaxis-inspired cellular primitives for self-organizing shape formation. This chapter details our initial effort to create Morphogenetic Primitives (MPs), software agents that may be programmed to self-organize into user-specified 2D shapes. The interactions of MPs are inspired by chemotaxis-driven aggregation behaviors exhibited by actual living cells. Cells emit a chemical into their environment. Each cell responds to the stimulus by moving in the direction of the gradient of the cumulative chemical field detected at its surface. The artificial chemical fields of individual MPs are explicitly defined as mathematical functions. Genetic programming is used to discover the chemical field functions that produce an automated shape formation capability. We describe the cell-based behaviors of MPs and a distributed genetic programming method that discovers the chemical fields needed to produce macroscopic shapes from simple aggregating primitives. Several examples of aggregating MPs demonstrate that chemotaxis is an effective paradigm for spatial self-organization algorithms
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Details
- Title
- Chemotaxis-Inspired Cellular Primitives for Self-Organizing Shape Formation
- Creators
- Linge Bai - Drexel UniversityDavid E. Breen - Drexel University
- Contributors
- R Doursat (Editor)H Sayama (Editor)O Michel (Editor)
- Publication Details
- Morphogenetic Engineering, pp 209-237
- Series
- Understanding Complex Systems Springer Complexity
- Publisher
- Springer Nature; BERLIN
- Number of pages
- 29
- Resource Type
- Book chapter
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000318316200009
- Other Identifier
- 991019168773004721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Automation & Control Systems
- Computer Science, Artificial Intelligence
- Robotics