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Found 6 papers, 0 papers with code
TRAC: A Textual Benchmark for Reasoning about Actions and Change
Reasoning about actions and change (RAC) is essential to understand and interact with the ever-changing environment.
Learning Visual Planning Models from Partially Observed Images
Although a number of approaches have been developed for learning planning models from fully observed unstructured data (e. g., images), in many scenarios raw observations are often incomplete.
Gradient-Based Mixed Planning with Symbolic and Numeric Action Parameters
In this paper, we propose a novel algorithm framework to solve numeric planning problems mixed with logical relations and numeric changes based on gradient descent.
Structural Similarity of Boundary Conditions and an Efficient Local Search Algorithm for Goal Conflict Identification
By taking experiments on a set of cases, we show that LOGION effectively exploits the structural similarity of BCs.
Refining HTN Methods via Task Insertion with Preferences
Hierarchical Task Network (HTN) planning is showing its power in real-world planning.
Representation Learning for Classical Planning from Partially Observed Traces
The experimental results show that the domain models learned by our approach are much more effective on solving real planning problems.
