Soft Actor Critic Swing Up of a Real Inverted Pendulum on a Cart

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dc.contributor.authorRaniero Humberto Calderon
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T15:35:58Z
dc.date.available2026-03-22T15:35:58Z
dc.date.issued2023
dc.descriptionCitaciones: 1
dc.description.abstractThe inverted pendulum, is a classical experiment widely used as a benchmark for research in control systems, due to its challenging dynamics. In this paper, Deep Reinforcement Learning is used to control a real inverted pendulum on a cart. The Soft Actor Critic algorithm with automatic entropy tuning is used to train an agent capable of acting as a controller. The agent is trained on real data collected on an episodic basis and learns to carry out the swing up control task successfully.
dc.identifier.doi10.53375/icmame.2023.403
dc.identifier.urihttps://doi.org/10.53375/icmame.2023.403
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/53307
dc.language.isoen
dc.sourceHigher University of San Andrés
dc.subjectInverted pendulum
dc.subjectSwing
dc.subjectComputer science
dc.subjectBenchmark (surveying)
dc.subjectDouble inverted pendulum
dc.subjectControl theory (sociology)
dc.subjectArtificial intelligence
dc.subjectReinforcement learning
dc.subjectController (irrigation)
dc.subjectTask (project management)
dc.titleSoft Actor Critic Swing Up of a Real Inverted Pendulum on a Cart
dc.typearticle

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