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Found 3 papers, 1 papers with code
Integrating Deep Reinforcement and Supervised Learning to Expedite Indoor Mapping
Each one helps to improve the decision making through use of the learned structural statistics of the environment, and both, being realized as neural networks, ensure a constant calculation time.
Deep-Learning-Aided Path Planning and Map Construction for Expediting Indoor Mapping
When the prediction is integrated in both path planning and map construction processes it is shown that the mapping time may in some cases be cut by over 50%.
Probabilistic Gathering Of Agents With Simple Sensors
Two types of motion are considered: when no peers are detected behind them, either the agents perform unit jumps forward, or they start to move with unit speed while continuously sensing their back half-plane, and stop whenever another agent appears there.
Multiagent Systems
