State alignment-based imitation learning
WebAbstract: We present a simple and effective algorithm designed to address the covariate shift problem in imitation learning. It operates by training an ensemble of policies on the … WebNov 13, 2024 · imitation learning (OOD-IL), which relaxes the assumption to that the demonstrator and the imitator have the same state spaces but could hav e different action spaces and dynamics. OOD-IL...
State alignment-based imitation learning
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WebHere we propose SAPIEN Manipulation Skill Benchmark (ManiSkill) to benchmark manipulation skills over diverse objects in a full-physics simulator. 97 Paper Code State … WebIn this paper, we move toward a more realistic setting and explore state-only imitation learning. To tackle this setting, we train an inverse dynamics model and use it to predict actions for state-only demonstrations. ... Liu F., Ling Z., Mu T., and Su H., “ State alignment-based imitation learning,” in ICLR, 2024. Google Scholar [31 ...
WebState Alignment-based Imitation Learning We propose a state-based imitation learning method for cross-morphology imitation learning, by considering both the state visitation … WebApr 14, 2024 · An efficient charging time forecasting reduces the travel disruption that drivers experience as a result of charging behavior. Despite the machine learning algorithm’s success in forecasting future outcomes in a range of applications (travel industry), estimating the charging time of an electric vehicle (EV) is relatively novel. It can …
WebJun 8, 2024 · In this work, we propose a two-phase, autonomous imitation learning technique called behavioral cloning from observation (BCO), that aims to provide improved performance with respect to both of... WebWe propose a novel state alignment-based imitation learning method to train the imitator by following the state sequences in the expert demonstrations as much as possible. The …
WebOct 23, 2024 · 7.2 State-Only Imitation Learning. Besides state-action imitation, we also evaluate the State-Only Imitation Learning (SOIL) algorithm which does using action information from demonstrations. SOIL extends DAPG to the state-only imitation setting by learning an inverse model \(h_\phi \) with the collected trajectories when running the …
WebFeb 4, 2024 · We propose State Matching Offline DIstribution Correction Estimation (SMODICE), a novel and versatile algorithm for offline imitation learning (IL) via state-occupancy matching. We show that the SMODICE objective admits a simple optimization procedure through an application of Fenchel duality and an analytic solution in tabular … cheviots nursing homeWeb1.6 Formulation of the Imitation Learning Problem . . . . . 18 2 Design of Imitation Learning Algorithms 20 2.1 Design Choices for Imitation Learning Algorithms . . . 20 2.2 Behavioral Cloning and Inverse Reinforcement Learning 24 ii good stead synonymWebWe propose a novel state alignment-based imitation learning method to train the imitator to follow the state sequences in expert demonstrations as much as possible. The state … cheviots mapWebWe formalize the Domain Adaptive Imitation Learning (DAIL) problem, which is a unified framework for imitation learning in the presence of viewpoint, embodiment, and dynamics mismatch. ... Generative Adversarial MDP Alignment (GAMA), to learn state and action correspondences ... Liu, F., Ling, Z., Mu, T., and Su, H. State alignment-based ... good stays hotel san ignacioWebDec 6, 2024 · Under a mild assumption that local states shall still be partially aligned under a dynamics mismatch, we propose imitation learning with horizon-adaptive inverse dynamics (HIDIL) that matches the simulator states with expert states in a H-step horizon and accurately recovers actions based on inverse dynamics policies. good stead for this jobWebJan 8, 2024 · Over the last 30 years, Imitation Learning has advanced significantly and been used to solve difficult tasks ranging from Autonomous Driving to playing Atari games. In … good stead defineWebApr 7, 2024 · Learning by imitation is a well-known and powerful mechanism in the cognitive development of children (Tomasello et al., 1993; Meltzoff, 1995). Similar to learning in children, our robots could acquire motor skills by learning from demonstrations. cheviot to blenheim