RT Journal Article
T1 Synthetic collective intelligence.
A1 Solé, Ricard V.
A1 Rodríguez-Amor, Daniel
A1 Durán-Nebreda, Salva
A1 Conde-Pueyo, Núria
A1 Carbonell-Ballesteros, Max
A1 Montañez, Raúl
K1 Autómatas celulares
K1 Biología sintética
K1 Inteligencia artificial
AB Intelligent systems have emerged in our biosphere in different contexts and achieving different levels of complexity. The requirement of communication in a social context has been in all cases a determinant. The human brain, probably co-evolving with language, is an exceedingly successful example. Similarly, social insects complex collective decisions emerge from information exchanges between many agents. The difference is that such processing is obtained out of a limited individual cognitive power. Computational models and embodied versions using non-living systems, particularly involving robot swarms, have been used to explore the potentiality of collective intelligence. Here we suggest a novel approach to the problem grounded in the genetic engineering of unicellular systems, which can be modified in order to interact, store memories or adapt to external stimuli in collective ways. What we label as Synthetic Swarm Intelligence defines a parallel approach to the evolution of computation and swarm intelligence and allows to explore potential embodied scenarios for decision making at the microscale. Here, we consider several relevant examples of collective intelligence and their synthetic organism counterparts.
PB Elsevier
YR 2016
FD 2016
LK https://hdl.handle.net/10630/32279
UL https://hdl.handle.net/10630/32279
LA eng
NO TY  - JOUR T1  - Synthetic collective intelligence AU  - Solé, Ricard AU  - Amor, Daniel R. AU  - Duran-Nebreda, Salva AU  - Conde-Pueyo, Núria AU  - Carbonell-Ballestero, Max AU  - Montañez, Raúl JO  - Biosystems VL  - 148 SP  - 47 EP  - 61 PY  - 2016 DA  - 2016/10/01/ T2  - What Synthetic Biology can offer to Artificial Intelligence SN  - 0303-2647 DO  - https://doi.org/10.1016/j.biosystems.2016.01.002 UR  - https://www.sciencedirect.com/science/article/pii/S0303264716300028 KW  - Synthetic biology KW  - Swarm intelligence KW  - Evolution KW  - Social insects KW  - Cellular machines AB  - Intelligent systems have emerged in our biosphere in different contexts and achieving different levels of complexity. The requirement of communication in a social context has been in all cases a determinant. The human brain, probably co-evolving with language, is an exceedingly successful example. Similarly, social insects complex collective decisions emerge from information exchanges between many agents. The difference is that such processing is obtained out of a limited individual cognitive power. Computational models and embodied versions using non-living systems, particularly involving robot swarms, have been used to explore the potentiality of collective intelligence. Here we suggest a novel approach to the problem grounded in the genetic engineering of unicellular systems, which can be modified in order to interact, store memories or adapt to external stimuli in collective ways. What we label as Synthetic Swarm Intelligence defines a parallel approach to the evolution of computation and swarm intelligence and allows to explore potential embodied scenarios for decision making at the microscale. Here, we consider several relevant examples of collective intelligence and their synthetic organism counterparts. ER  -
NO Política de acceso abierto tomada de: https://v2.sherpa.ac.uk/id/publication/15499
NO ERC Advanced Grant Number 294294 from the EU seventh framework program (SYNCOM), by grants of the Botin Foundation, by Banco Santander through its Santander Universities Global Division and by the Santa Fe Institute
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 3 mar 2026