AINov 4, 2021
Imagine Networks
arXiv:2111.03048v51 citations
Originality Synthesis-oriented
AI Analysis
This addresses the problem of data generation for AI systems, but appears incremental as it builds on existing techniques like GANs and reinforcement learning.
The paper introduces an 'imagine network' that simulates itself through artificial association networks, combining discriminator and reinforcement learning models to learn from datasets and generate new data samples.
In this paper, we introduce an imagine network that can simulate itself through artificial association networks. Association, deduction, and memory networks are learned, and a network is created by combining the discriminator and reinforcement learning models. This model can learn various datasets or data samples generated in environments and generate new data samples.