From the 1 of 7 linked papers with an AI index.
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Macro-Operator Generation and Predicate Selection for TAMP Operator Learning
Can Emir Bora, Emre Ugur
Creating symbolic operators by hand is one of the main bottlenecks in deploying Task and Motion Planning systems (TAMP). Recent works show that these operators can instead be learn…
Task Parameter Extrapolation via Learning Inverse Tasks from Forward Demonstrations
Serdar Bahar, Fatih Dogangun, Matteo Saveriano +2
The paper introduces a joint learning framework that builds a shared representation of forward and inverse tasks, enabling robots to infer and execute inverse tasks from only forwa…
Joint Discovery of Object and Action Symbols through Effect Prediction for Robotic Manipulation Planning
Burcu Kilic, Berke Kartal, Fatih Dogangun +2
To perform complex manipulation planning, autonomous robots are required to abstract continuous, high-dimensional sensorimotor interactions into discrete object and action represen…
Trajectory Learning with Graph Representations for Social Robot Navigation
Berke Kartal, Burcu Kilic, Yigit Yildirim +1
Autonomous mobile robots are expected to exhibit socially compliant navigation for minimizing pedestrian disturbance. While capturing social interactions and incorporating pedestri…
Bilevel Planning with Learned Symbolic Abstractions from Interaction Data
Fatih Dogangun, Burcu Kilic, Serdar Bahar +1
Intelligent agents must reason over both continuous dynamics and discrete representations to generate effective plans in complex environments. Previous studies have shown that symb…
Predictability-Based Curiosity-Guided Action Symbol Discovery
Burcu Kilic, Alper Ahmetoglu, Emre Ugur
Discovering symbolic representations for skills is essential for abstract reasoning and efficient planning in robotics. Previous neuro-symbolic robotic studies mostly focused on di…