This paper presents a novel approach to imitation learning that we call Inverse Optimal Heuristic Control (IOHC) which capitalizes on the strengths of both paradigms by allowing long-horizon, planning style reasoning in a low dimensional space, while enabling a high dimensional additional set of features to guide ...
This pa- per presents inverse optimal heuristic control. (IOHC), a novel approach to imitation learn- ing that capitalizes on the strengths of both paradigms.
This paper presents inverse optimal heuristic control (IOHC), a novel approach to imitation learning that capitalizes on the strengths of both paradigms. It ...
This pa- per presents inverse optimal heuristic control (IOHC), a novel approach to imitation learn- ing that capitalizes on the strengths of both paradigms. It ...
This paper presents inverse optimal heuristic control (IOHC), a novel approach to imitation learning that capitalizes on the strengths of both paradigms. It ...
To circumvent the ambiguous annotation of human driving decisions, our method learns high-level driving decisions by imitating low-level control behaviors. We ...
We develop a general framework for inverse op- timal control that distinguishes between rational- izing demonstrated behavior and imitating induc-.
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Inverse optimal heuristic control (IOHC) addresses high-dimensional imitation learning problems by capitalizing on the idea that many of these problems can be ...
Inverse Reinforcement Learning. (IRL) specifically addresses the question of inferring the cost function being optimized [18, 19, 29] or approximately optimized ...
Find a reward function such that the teacher maximally outperforms all previously found controllers. ▫ Find optimal control policy πi for the current guess of ...