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Qualitative control of cart and pole on uneven terrain [Elektronski vir]Šoberl, Domen ; Bratko, Ivan, računalništvoQualitative modelling can be applied to the control of dynamic systems by following these steps: (1) learning a qualitative model of the controlled dynamic system from the system’s behaviors in time, ... (2) using the learned model for deriving a qualitative plan for the control task, and (3) executing the qualitative plan on the actual dynamic system. This approach has been demonstrated in the usual cart-pole control domain to be much more efficient in terms of learning sample size than usual variants of reinforcement learning. In this paper, we generalize the cart-pole problem to uneven terrain, such driving over a crater. We study whether the learned flat-surface qualitative controller can be advantageously transferred to the tasks of negotiating uneven terrain. Experiments show that the flat-surface qualitative controller is remarkably robust on the new, more difficult tasks.Type of material - conference contributionPublish date - 2022Language - englishCOBISS.SI-ID - 120894467
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Database name | Field | Year |
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Šoberl, Domen | 31917 |
Bratko, Ivan, računalništvo | 02275 |
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