Cumulative Stabilization Probabilities During PPO Learning: A Paired Reward Study for Cart-Pendulum Swing-Up

This simulation study investigates how the cumulative probability of successful cart–pendulum swing-up and sustained stabilization changes with training progress and physical evaluation time. The target quantity, H(g,t), measures the probability that a controller has completed its first qualifying stabilization interval by time t at training generation g. Two reward formulations are compared using 100 paired training seeds, 1,000 PPO rollout/update generations per controller, and full 20-second evaluations every ten generations. The simulator uses fully nonlinear uniform-rod dynamics. Success requires a simultaneous two-second hold within specified cart-position, cart-velocity, upright-angle and angular-velocity tolerances. At the final generation, 68/100 bounded-reward controllers and 52/100 quadratic-reward controllers succeeded by 20 seconds. The observed paired difference was 16 percentage points, with a conservative 95% interval of −3.461 to +34.184 points. Quadratic achieved substantial success earlier during training but subsequently regressed. Final completion-time curves crossed, showing that neither reward uniformly dominated. The comparison is a follow-up using an already observed bounded-reward reference arm. Failures, censoring and learning regressions are retained. Supporting material provides event data, source code, configurations and reproducible analysis.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-01
DOI
https://doi.org/10.5281/zenodo.23808855
Primary Topic
Reinforcement Learning in Robotics
Type
preprint
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preprint

Cumulative Stabilization Probabilities During PPO Learning: A Paired Reward Study for Cart-Pendulum Swing-Up

Shaikhislam Askanbay
1 links
Zenodo (CERN European Organization for Nuclear Research)
Reinforcement Learning in Robotics
preprint

Cumulative Stabilization Probabilities During PPO Learning: A Paired Reward Study for Cart-Pendulum Swing-Up

Shaikhislam Askanbay
preprint en

Abstract

This simulation study investigates how the cumulative probability of successful cart–pendulum swing-up and sustained stabilization changes with training progress and physical evaluation time. The target quantity, H(g,t), measures the probability that a controller has completed its first qualifying stabilization interval by time t at training generation g. Two reward formulations are compared using 100 paired training seeds, 1,000 PPO rollout/update generations per controller, and full 20-second evaluations every ten generations. The simulator uses fully nonlinear uniform-rod dynamics. Success requires a simultaneous two-second hold within specified cart-position, cart-velocity, upright-angle and angular-velocity tolerances. At the final generation, 68/100 bounded-reward controllers and 52/100 quadratic-reward controllers succeeded by 20 seconds. The observed paired difference was 16 percentage points, with a conservative 95% interval of −3.461 to +34.184 points. Quadratic achieved substantial success earlier during training but subsequently regressed. Final completion-time curves crossed, showing that neither reward uniformly dominated. The comparison is a follow-up using an already observed bounded-reward reference arm. Failures, censoring and learning regressions are retained. Supporting material provides event data, source code, configurations and reproducible analysis.

Zenodo (CERN European Organization for Nuclear Research)
Reinforcement Learning in Robotics
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