Towards Autonomous Grading In The Real World

no code implementations • 13 Jun 2022 • Yakov Miron, Chana Ross, Yuval Goldfracht, Chen Tessler, Dotan Di Castro

As the heuristics are capable of successfully solving the task in the simulated environment, we show they can be leveraged to guide a learning agent which can generalize and solve the task both in simulation and in a scaled prototype environment.

AGPNet -- Autonomous Grading Policy Network

no code implementations • 20 Dec 2021 • Chana Ross, Yakov Miron, Yuval Goldfracht, Dotan Di Castro

In this work, we establish heuristics and learning strategies for the autonomous control of a dozer grading an uneven area studded with sand piles.

Contrastive Learning reinforcement-learning +1

SOLO: Search Online, Learn Offline for Combinatorial Optimization Problems

no code implementations • 4 Apr 2021 • Joel Oren, Chana Ross, Maksym Lefarov, Felix Richter, Ayal Taitler, Zohar Feldman, Christian Daniel, Dotan Di Castro

This method can equally be applied to both the offline, as well as online, variants of the combinatorial problem, in which the problem components (e. g., jobs in scheduling problems) are not known in advance, but rather arrive during the decision-making process.

Combinatorial Optimization Decision Making +3