Abstract Constraint-based offline reinforcement learning (RL) involves policy constraints or imposing penalties on the value function to mitigate overestimation errors caused by distributional shift. This paper focuses on a limitation in ex... Read More
The ability to predict the feasibility of manufacturing parts significantly enhances production efficiency and reduces costs in the manufacturing industry. Leveraging this technology, the laboratory of the Department of Industrial Engineeri... Read More
A research team, led by Professor Seungryul Baek at the Graduate School of Artificial Intelligence, UNIST, has achieved remarkable success in the HANDS workshop challenge, held in conjunction with the 2024 European Conference on Computer Vi... Read More
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