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Found 5 papers, 1 papers with code
Scaling up ML-based Black-box Planning with Partial STRIPS Models
A popular approach for sequential decision-making is to perform simulator-based search guided with Machine Learning (ML) methods like policy learning.
Exploiting Learned Policies in Focal Search
In this paper, we propose various ways in which such policies can be integrated into Focal Search, assuming that the policy is a neural network classifier.
How a General-Purpose Commonsense Ontology can Improve Performance of Learning-Based Image Retrieval
Consequently, a main conclusion of this work is that general-purpose commonsense ontologies improve performance on visual reasoning tasks when properly filtered to select meaningful visual relations.
Finite LTL Synthesis is EXPTIME-complete
LTL synthesis -- the construction of a function to satisfy a logical specification formulated in Linear Temporal Logic -- is a 2EXPTIME-complete problem with relevant applications in controller synthesis and a myriad of artificial intelligence applications.
Avoiding and Escaping Depressions in Real-Time Heuristic Search
When the objective is to find a single solution by running the real-time search algorithm once, we show that daLSS-LRTA* and daRTAA* outperform their predecessors sometimes by one order of magnitude.
