TY - CHAP
T1 - Interacting agents in a network for in silico modeling of nature-inspired smart systems
AU - Murthy, V. Kris
AU - Krishnamurthy, E. V.
PY - 2007
Y1 - 2007
N2 - An interacting multi-agent system in a network can model the evolution of a Nature-Inspired Smart System (NISS) exhibiting the four salient properties: (i) Collective, coordinated and efficient (ii) Self-organization and emergence (iii) Power law scaling or scale invariance under emergence (iv) Adaptive, fault tolerant and resilient against damage. We explain how these basic properties can arise among agents through random enabling, inhibiting, preferential attachment and growth of a multiagent system. The quantitative understanding of a Smart system with an arbitrary interactive topology is extremely difficult. However, for specific applications and a pre-defined static interactive topology among the agents, the quantitative parameters can be obtained through simulation to build a specific NISS. Further developments of agent technology will be of great value to model, simulate and animate, many phenomena in Systems biology - pattern formation, cellular dynamics, cell motility, growth and development biology, and can provide for improved capability in complex systems modelling. Also agents will serve as useful tools to model, design and develop biomorphic robots and neuromorphic chips.
AB - An interacting multi-agent system in a network can model the evolution of a Nature-Inspired Smart System (NISS) exhibiting the four salient properties: (i) Collective, coordinated and efficient (ii) Self-organization and emergence (iii) Power law scaling or scale invariance under emergence (iv) Adaptive, fault tolerant and resilient against damage. We explain how these basic properties can arise among agents through random enabling, inhibiting, preferential attachment and growth of a multiagent system. The quantitative understanding of a Smart system with an arbitrary interactive topology is extremely difficult. However, for specific applications and a pre-defined static interactive topology among the agents, the quantitative parameters can be obtained through simulation to build a specific NISS. Further developments of agent technology will be of great value to model, simulate and animate, many phenomena in Systems biology - pattern formation, cellular dynamics, cell motility, growth and development biology, and can provide for improved capability in complex systems modelling. Also agents will serve as useful tools to model, design and develop biomorphic robots and neuromorphic chips.
UR - http://www.scopus.com/inward/record.url?scp=34547779910&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-73177-1_7
DO - 10.1007/978-3-540-73177-1_7
M3 - Chapter
SN - 354073175X
SN - 9783540731757
T3 - Studies in Computational Intelligence
SP - 177
EP - 231
BT - Computational Intelligence for Agent-based Systems
A2 - Lee, Reymond
A2 - Loia, Vincenzo
ER -