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Generator and discriminator losses for a collection of K = 16 competing agents.

Generator and discriminator losses for a collection of K = 16 competing agents.

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Fig. 1: Two competing networks N (1) and N (2) .
Fig. 2: Generator and discriminator losses for a collection of K = 16...
Competing Adaptive Networks
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  • Mar 2021
Adaptive networks have the capability to pursue solutions of global stochastic optimization problems by relying only on local interactions within neighborhoods. The diffusion of information through repeated interactions allows for globally optimal behavior, without the need for central coordination. Most existing strategies are developed for cooper...
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Context 1
... fits into the framework considered in this work. We illustrate performance on simple, fully-connected, feedforward neural networks trained using Alg. 1 and depict loss evolution in Fig. 2 and the evolution of generated images in 3. ...
Context 2
... fits into the framework considered in this work. We illustrate performance on simple, fully-connected, feedforward neural networks trained using Alg. 1 and depict loss evolution in Fig. 2 and the evolution of generated images in 3. ...

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