Dec 6, 2023 · We show that there are three general classes of planning problems, in terms of the growth of circuit width and depth as a function of the number ...
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Nov 2, 2023 · This paper focuses on formalizing what class of planning problems can be solved by a relational neural networks. It aims to bridge the gap ...
Dec 6, 2023 · Goal-conditioned policies are generally understood to be “feed-forward” circuits, in the form of neural networks that map from the current ...
What Planning Problems Can A Relational Neural Network Solve? · Setup · Assembly3 · BlocksWorld-Clear · Logistics · About · Releases · Packages 0 · Languages.
May 30, 2024 · We show that there are three general classes of planning problems, in terms of the growth of circuit width and depth as a function of the number ...
Goal-conditioned policies are like cheat codes for planning problems, helping agents decide what actions to take. This paper explains how neural networks ...
@InProceedings{LIS334, title = {What Planning Problem Can A Relational Neural Network Solve}, author = {Jiayuan Mao, Tomás Lozano-Pérez, Joshua B. Tenenbaum, ...
We propose a novel relational graph neural network for situation recognition, which explicitly models the triplet relationships between the activity and the ...
[PDF] Learning Generalized Relational Heuristic Networks for Model ...
aair-lab.github.io › ks_aaai21
Our overall approach for model-agnostic planning in- volves solving these learning problems by training a Gen- eralized Heuristic Network (GHN) (Sec. 3) and ...
Recurrent Relational Networks for Complex Relational Reasoning
www.researchgate.net › ... › Reasoning
Relational networks, introduced by Santoro et al. (2017), add the capacity for relational reasoning to deep neural networks, but are limited in the complexity ...