Download Transfer Learning for Multiagent by Felipe Leno Da Silva (.PDF)

Transfer Learning for Multiagent Reinforcement Learning Systems (Synthesis Lectures on Artificial Intelligence and Machine Le) by Felipe Leno Da Silva
Requirements: .PDF reader, 9 MB
Overview: Learning to solve sequential decision-making tasks is difficult. Humans take years exploring the environment essentially in a random way until they are able to reason, solve difficult tasks, and collaborate with other humans towards a common goal. Artificial Intelligent agents are like humans in this aspect. Reinforcement Learning (RL) is a well-known technique to train autonomous agents through interactions with the environment. Unfortunately, the learning process has a high sample complexity to infer an effective actuation policy, especially when multiple agents are simultaneously actuating in the environment.
Genre: Non-Fiction > Educational

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