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Found 8 papers, 0 papers with code
Rethinking Urban Flood Risk Assessment By Adapting Health Domain Perspective
The proposed perspective focuses on three pillars for examining flood risk: (1) inherent susceptibility, (2) mitigation strategies, and (3) external stressors.
Deep Learning-driven Community Resilience Rating based on Intertwined Socio-Technical Systems Features
The interpretability of the model outcomes enables feature analysis for specifying the determinants of resilience in areas within each resilience level, allowing for the identification of specific resilience enhancement strategies.
Unsupervised Graph Deep Learning Reveals Emergent Flood Risk Profile of Urban Areas
Urban flood risk emerges from complex and nonlinear interactions among multiple features related to flood hazard, flood exposure, and social and physical vulnerabilities, along with the complex spatial flood dependence relationships.
Decision-Making Among Bounded Rational Agents
Using both simulated and real-world experiments in multi-robot navigation tasks, we demonstrate that the resulting framework allows the robots to reason about different levels of rational behaviors of other agents and compute a reasonable strategy under its computational constraint.
Online Planning in Uncertain and Dynamic Environment in the Presence of Multiple Mobile Vehicles
We first predict the future state distributions of other vehicles to account for their uncertain behaviors affected by the time-varying disturbances.
Kernel Taylor-Based Value Function Approximation for Continuous-State Markov Decision Processes
We propose a principled kernel-based policy iteration algorithm to solve the continuous-state Markov Decision Processes (MDPs).
Reachable Space Characterization of Markov Decision Processes with Time Variability
We propose a solution to a time-varying variant of Markov Decision Processes which can be used to address decision-theoretic planning problems for autonomous systems operating in unstructured outdoor environments.
A Spatio-Temporal Representation for the Orienteering Problem with Time-Varying Profits
Different from most existing works where the profits are assumed to be static, in this work we investigate a variant that has arbitrary time-dependent profits.
