inverse reinforcement learning

Massively Scalable Inverse Reinforcement Learning in Google Maps ICLR 2024 Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models NeurIPS 2024 Measuring Goal-Directedness NeurIPS 2024 Meta-Inverse Reinforcement Learning for Mean Field Games via Probabilistic Context Variables AAAI 2024 Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms ICML 2024 One Shot Inverse Reinforcement Learning for Stochastic Linear Bandits UAI 2024 Pareto Inverse Reinforcement Learning for Diverse Expert Policy Generation IJCAI 2024 Quantifying the Sensitivity of Inverse Reinforcement Learning to Misspecification ICLR 2024 Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL ICLR 2024 Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces NeurIPS 2024 Recent Advancements in Inverse Reinforcement Learning AAAI 2024 Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment NeurIPS 2024 Simplifying Constraint Inference with Inverse Reinforcement Learning NeurIPS 2024 SPRINQL: Sub-optimal Demonstrations driven Offline Imitation Learning NeurIPS 2024 Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning NeurIPS 2024 Towards the Transferability of Rewards Recovered via Regularized Inverse Reinforcement Learning NeurIPS 2024 A Bayesian Approach to Robust Inverse Reinforcement Learning CoRL 2023 A Data-Driven State Aggregation Approach for Dynamic Discrete Choice Models UAI 2023 A Pragmatic Look at Deep Imitation Learning ACML 2023 BC-IRL: Learning Generalizable Reward Functions from Demonstrations ICLR 2023 Benchmarking Constraint Inference in Inverse Reinforcement Learning ICLR 2023 Causal Imitation Learning via Inverse Reinforcement Learning ICLR 2023 CLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning ICLR 2023 Coherent Soft Imitation Learning NeurIPS 2023 Explanation-Guided Reward Alignment IJCAI 2023