No account yet ?

What is Distributed Artificial Intelligence ?

Distributed artificial intelligence is an approach to solving complex learning, planning and decision-making problems.

Distributed artificial intelligence is capable of exploiting large-scale computing and the spatial distribution of computing resources.

These properties allow it to solve problems requiring the processing of very large data sets.

Systems that leverage distributed artificial intelligence work with autonomous learning processing nodes called agents.

The nodes used by the distributed artificial intelligence can act independently, partial solutions are also integrated by the communication between the nodes and often asynchronously.

Due to their scale, systems that use distributed artificial intelligence are robust, elastic, and loosely coupled.

Systems that use distributed artificial intelligence are designed to adapt to changes in the problem definition or underlying data sets due to scale and difficulty of redeployment.

In systems that use distributed AI, there is no need for all relevant data to be aggregated in one place unlike monolithic or centralized AI systems that have tightly coupled and geographically close processing nodes.

Therefore, systems that use distributed artificial intelligence often operate on subsamples or hashed impressions of very large datasets.

The source data set can change or be updated during the execution of a system that uses distributed artificial intelligence.