[HTML][HTML] Risk-aware shielding of partially observable monte carlo planning policies
Abstract Partially Observable Monte Carlo Planning (POMCP) is a powerful online algorithm
that can generate approximate policies for large Partially Observable Markov Decision …
that can generate approximate policies for large Partially Observable Markov Decision …
Rule-based shielding for partially observable Monte-Carlo planning
Abstract Partially Observable Monte-Carlo Planning (POMCP) is a powerful online algorithm
able to generate approximate policies for large Partially Observable Markov Decision …
able to generate approximate policies for large Partially Observable Markov Decision …
Online partial conditional plan synthesis for POMDPs with safe-reachability objectives: Methods and experiments
The framework of partially observable Markov decision processes (POMDPs) offers a
standard approach to model uncertainty in many robot tasks. Traditionally, POMDPs are …
standard approach to model uncertainty in many robot tasks. Traditionally, POMDPs are …
Multi-robot coordination under temporal uncertainty
C Street - 2022 - ora.ox.ac.uk
Sources of temporal uncertainty affect the duration and start time of robot actions during
execution. For example, mobile robots may slip on uneven terrain, slowing them down. The …
execution. For example, mobile robots may slip on uneven terrain, slowing them down. The …
Rule-Based Policy Interpretation and Shielding for Partially Observable Monte Carlo Planning
Abstract Partially Observable Monte Carlo Planning (POMCP) is a powerful online algorithm
that can generate approximate policies for large Partially Observable Markov Decision …
that can generate approximate policies for large Partially Observable Markov Decision …