Papers › C-Learning: Horizon-Aware Cumulative Accessibility Estimation

C-Learning: Horizon-Aware Cumulative Accessibility Estimation

24 Nov 2020ICLR 2021 1arXiv:2011.12363archive 2025-07-28

Panteha Naderian, Gabriel Loaiza-Ganem, Harry J. Braviner, Anthony L. Caterini, Jesse C. Cresswell, Tong Li, Animesh Garg

Multi-goal reaching is an important problem in reinforcement learning needed to achieve algorithmic generalization. Despite recent advances in this field, current algorithms suffer from three major challenges: high sample complexity, learning only a single way of reaching the goals, and difficulties in solving complex motion planning tasks. In order to address these limitations, we introduce the concept of cumulative accessibility functions, which measure the reachability of a goal from a given state within a specified horizon. We show that these functions obey a recurrence relation, which enables learning from offline interactions. We also prove that optimal cumulative accessibility functions are monotonic in the planning horizon. Additionally, our method can trade off speed and reliability in goal-reaching by suggesting multiple paths to a single goal depending on the provided horizon. We evaluate our approach on a set of multi-goal discrete and continuous control tasks. We show that our method outperforms state-of-the-art goal-reaching algorithms in success rate, sample complexity, and path optimality. Our code is available at https://github.com/layer6ai-labs/CAE, and additional visualizations can be found at https://sites.google.com/view/learning-cae/.

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CNetworkDisc layer6ai-labs/CAE/algo/C_learning_Discrete.py official repository ran no licence file found · pointer only · fc794f0fdca634e5 · report
DiscreteDubinsCar layer6ai-labs/CAE/algo/C_learning_Discrete.py official repository ran no licence file found · pointer only · 7937018ae2dc8366 · report
PrecipiceEnv layer6ai-labs/CAE/algo/C_learning_Discrete.py official repository ran no licence file found · pointer only · 63ac790824d5cd9f · report
normalize layer6ai-labs/cae/evaluate/sim.py official repository ran · violated contract no licence file found · pointer only · 53e96986bfd3af3f · report
sample_long_range_transitions layer6ai-labs/CAE/algo/C_learning_Discrete.py official repository ran · our draft was wrong no licence file found · pointer only · b9680333054efb6a · report
CLearningDiscrete layer6ai-labs/CAE/algo/C_learning_Discrete.py official repository unverified no licence file found · pointer only · 4d06e3f3cda2f9f9 · report
MiniMazeEnv layer6ai-labs/CAE/algo/C_learning_Discrete.py official repository unverified no licence file found · pointer only · 7e08a83cc1613540 · report

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Continuous ControlMotion Planningcontinuous-control

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