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Found 7 papers, 0 papers with code
Planning and Learning: Path-Planning for Autonomous Vehicles, a Review of the Literature
We describe briefly the concept of reinforcement learning algorithms and some approaches designed to date.
Solving Disjunctive Temporal Networks with Uncertainty under Restricted Time-Based Controllability using Tree Search and Graph Neural Networks
Moreover, we leverage a graph neural network as a heuristic for tree search guidance.
Time-based Dynamic Controllability of Disjunctive Temporal Networks with Uncertainty: A Tree Search Approach with Graph Neural Network Guidance
Scheduling in the presence of uncertainty is an area of interest in artificial intelligence due to the large number of applications.
Optimal Solving of Constrained Path-Planning Problems with Graph Convolutional Networks and Optimized Tree Search
More specifically, a graph neural network is used to assist the branch and bound algorithm in handling constraints associated with a desired solution path.
Learning off-road maneuver plans for autonomous vehicles
The proposed framework achieves significant improvement on known benchmarks in this controllability type over the performance of state-of-the-art works in a related controllability type.
Constrained Shortest Path Search with Graph Convolutional Neural Networks
In this paper, we focus on shortest path search with mandatory nodes on a given connected graph.
Learning-based Preference Prediction for Constrained Multi-Criteria Path-Planning
The uncertain criterion represents the feasibility of driving through the path without requiring human intervention.
