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Found 3 papers, 1 papers with code
Hierarchical Representations and Explicit Memory: Learning Effective Navigation Policies on 3D Scene Graphs using Graph Neural Networks
In this work, we present a reinforcement learning framework that leverages high-level hierarchical representations to learn navigation policies.
Bridging Scene Understanding and Task Execution with Flexible Simulation Environments
Significant progress has been made in scene understanding which seeks to build 3D, metric and object-oriented representations of the world.
A Comparison of Monte Carlo Tree Search and Mathematical Optimization for Large Scale Dynamic Resource Allocation
In this paper, we adapt both MCTS and MO to a problem inspired by tactical wildfire and management and undertake an extensive computational study comparing the two methods on large scale instances in terms of both the state and the action spaces.
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