Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Pettet, Geoffrey"'
Autor:
Wilbur, Michael, Kadir, Salah Uddin, Kim, Youngseo, Pettet, Geoffrey, Mukhopadhyay, Ayan, Pugliese, Philip, Samaranayake, Samitha, Laszka, Aron, Dubey, Abhishek
Many transit agencies operating paratransit and microtransit services have to respond to trip requests that arrive in real-time, which entails solving hard combinatorial and sequential decision-making problems under uncertainty. To avoid decisions th
Externí odkaz:
http://arxiv.org/abs/2203.15127
Decision-making under uncertainty (DMU) is present in many important problems. An open challenge is DMU in non-stationary environments, where the dynamics of the environment can change over time. Reinforcement Learning (RL), a popular approach for DM
Externí odkaz:
http://arxiv.org/abs/2202.13003
Autor:
Pettet, Geoffrey, Baxter, Hunter, Vazirizade, Sayyed Mohsen, Purohit, Hemant, Ma, Meiyi, Mukhopadhyay, Ayan, Dubey, Abhishek
Designing effective emergency response management (ERM) systems to respond to incidents such as road accidents is a major problem faced by communities. In addition to responding to frequent incidents each day (about 240 million emergency medical serv
Externí odkaz:
http://arxiv.org/abs/2202.11268
Resource allocation under uncertainty is a classical problem in city-scale cyber-physical systems. Consider emergency response as an example; urban planners and first responders optimize the location of ambulances to minimize expected response times
Externí odkaz:
http://arxiv.org/abs/2107.01292
Autor:
Vazirizade, Sayyed Mohsen, Mukhopadhyay, Ayan, Pettet, Geoffrey, Said, Said El, Baroud, Hiba, Dubey, Abhishek
Principled decision making in emergency response management necessitates the use of statistical models that predict the spatial-temporal likelihood of incident occurrence. These statistical models are then used for proactive stationing which allocate
Externí odkaz:
http://arxiv.org/abs/2106.08307
A classical problem in city-scale cyber-physical systems (CPS) is resource allocation under uncertainty. Typically, such problems are modeled as Markov (or semi-Markov) decision processes. While online, offline, and decentralized approaches have been
Externí odkaz:
http://arxiv.org/abs/2012.13300
Emergency response to incidents such as accidents, crimes, and fires is a major problem faced by communities. Emergency response management comprises of several stages and sub-problems like forecasting, resource allocation, and dispatch. The design o
Externí odkaz:
http://arxiv.org/abs/2010.07504
Autor:
Mukhopadhyay, Ayan, Pettet, Geoffrey, Vazirizade, Sayyed, Lu, Di, Said, Said El, Jaimes, Alex, Baroud, Hiba, Vorobeychik, Yevgeniy, Kochenderfer, Mykel, Dubey, Abhishek
In the last fifty years, researchers have developed statistical, data-driven, analytical, and algorithmic approaches for designing and improving emergency response management (ERM) systems. The problem has been noted as inherently difficult and const
Externí odkaz:
http://arxiv.org/abs/2006.04200
Autor:
Pettet, Geoffrey, Mukhopadhyay, Ayan, Kochenderfer, Mykel, Vorobeychik, Yevgeniy, Dubey, Abhishek
Emergency Response Management (ERM) is a critical problem faced by communities across the globe. Despite this, it is common for ERM systems to follow myopic decision policies in the real world. Principled approaches to aid ERM decision-making under u
Externí odkaz:
http://arxiv.org/abs/2001.07362
Autor:
Mukhopadhyay, Ayan, Pettet, Geoffrey, Samal, Chinmaya, Dubey, Abhishek, Vorobeychik, Yevgeniy
The problem of dispatching emergency responders to service traffic accidents, fire, distress calls and crimes plagues urban areas across the globe. While such problems have been extensively looked at, most approaches are offline. Such methodologies f
Externí odkaz:
http://arxiv.org/abs/1902.08274