What is Swarm Intelligence?
Swarm intelligence is drawing on examples from the natural world as models for decentralized learning and decision-making. Birds, bees, fish, ants, and other organisms make surprisingly complex decisions not as individuals, but as groups. Artificial intelligence applies similar principles for dynamic, aggregate analysis and conclusions.
How does swarm intelligence work?
Swarm intelligence is a form of collective learning and decision-making based on decentralized, self-organized systems. Natural examples are commonplace—flocks of birds and schools of fish act and react as groups, without instruction or direction from any single leader. Input from any one component can immediately alter the behavior of the entire group.
As a form of artificial intelligence, swarm intelligence comprises a network of endpoint devices capable of generating and processing data at the source. Relevant information that fits certain predetermined conditions can be shared immediately across the network, allowing individual agents to process and act on input from their peers without being dependent on a centralized data lake or decision matrix.
For example, self-driving vehicles able to gather and process traffic data could share it with other vehicles in the same traffic system, allowing them to react to changing traffic conditions in real time, adjusting their speed and routes to avoid road hazards or congestion.
Blockchain technology enables edge locations to share information and insights in a trusted manner, providing useful data to the network without compromising the privacy and security of its endpoints. This can be particularly important for medical and financial systems.
What are the benefits of swarm intelligence?
Swarm intelligence has a wide range of potential applications, from coordinated industrial-scale automation to smarter, safer healthcare and financial systems. When individual edge devices are able to recognize and share critical information with their peers, the entire network becomes smarter and more adaptable.
Swarm intelligence can be:
- Collaborative—Able to share information directly between devices.
- Adaptable—Able to recognize predetermined stimuli and categorize novel events.
- Flexible—Able to respond quickly to a variety of conditions affecting any agent in the system.
- Decentralized—Able to act either independently or collectively without central coordination or control.
- Responsive—Able to react immediately to local stimuli without latency.
- Self-organized—Able to adopt a variety of roles as needed in response to changing conditions.
- Self-correcting—Able to adapt and reorganize, compensating for faults and completing tasks even when individual agents fail.
- Secure—Able to share vital insights without compromising confidentiality or privacy requirements.
HPE and swarm intelligence
Dr. Eng Lim Goh, senior vice president and chief technology officer for artificial intelligence at Hewlett Packard Enterprise, is one of the world’s leading experts in swarm intelligence and swarm learning. Dr. Goh is a frequent contributor to Enterprise.nxt, where his observations on swarm intelligence offer insights into the future of enterprise computing.
Hewlett Packard Labs, the research and development arm of Hewlett Packard Enterprise, continues to drive innovation in technologies and applications for swarm intelligence and swarm learning.
Swarm intelligence has far-reaching implications for HPE offerings in the fields of artificial intelligence and machine learning. Organizations interested in implementing swarm intelligence will benefit from HPE’s existing offerings in AI/ML and edge computing, including HPE Apollo systems, HPE ProLiant servers, and HPE Edgeline Converged Edge systems.