首页|Investigators at University of Newcastle Describe Findings in Computational Intelligence (Optimal Actor-critic Policy With Optimized Training Datasets)
Investigators at University of Newcastle Describe Findings in Computational Intelligence (Optimal Actor-critic Policy With Optimized Training Datasets)
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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.”
CallaghanAustraliaAustralia and New ZealandComputational IntelligenceMachine LearningUniversity of Newcastle
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