Goal: A generalist combinatorial optimization agent learner
D Drakulic, S Michel, JM Andreoli - arXiv preprint arXiv:2406.15079, 2024 - arxiv.org
Machine Learning-based heuristics have recently shown impressive performance in solving
a variety of hard combinatorial optimization problems (COPs). However they generally rely …
a variety of hard combinatorial optimization problems (COPs). However they generally rely …
Fast-and-Frugal Text-Graph Transformers are Effective Link Predictors
Link prediction models can benefit from incorporating textual descriptions of entities and
relations, enabling fully inductive learning and flexibility in dynamic graphs. We address the …
relations, enabling fully inductive learning and flexibility in dynamic graphs. We address the …
Quality Diversity for Robot Learning: Limitations and Future Directions
Quality Diversity (QD) has shown great success in discovering high-performing, diverse
policies for robot skill learning. While current benchmarks have led to the development of …
policies for robot skill learning. While current benchmarks have led to the development of …