Robotics & Machine Learning Daily News2024,Issue(Jan.17) :42-42.

Investigators at University of Newcastle Describe Findings in Computational Intelligence (Optimal Actor-critic Policy With Optimized Training Datasets)

Robotics & Machine Learning Daily News2024,Issue(Jan.17) :42-42.

Investigators at University of Newcastle Describe Findings in Computational Intelligence (Optimal Actor-critic Policy With Optimized Training Datasets)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learning - Computational Intelligence have beenpublished. According to news reporting out of Callaghan, Australia, by NewsRx editors, research stated,“Actor-critic (AC) algorithms are known for their efficacy and high performance in solving reinforcementlearning problems, but they also suffer from low sampling efficiency. An AC based policy optimizationprocess is iterative and needs to access the agent-environment to evaluate and update the policy by rollingout the policy, collecting rewards and states (i.e. samples), and learning from them.”

Key words

Callaghan/Australia/Australia and New Zealand/Computational Intelligence/Machine Learning/University of Newcastle

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2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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