The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Joelle Pineau - One of the best experts on this subject based on the ideXlab platform.
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Tarmac: Targeted Multi-Agent Communication
arXiv: Learning, 2018Co-Authors: Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Michael G. Rabbat, Joelle PineauAbstract:We propose a targeted communication architecture for multi-agent reinforcement learning, where agents learn both what messages to send and whom to address them to while performing cooperative tasks in partially-observable environments. This targeting behavior is learnt solely from downstream task-specific reward without any communication supervision. We additionally augment this with a multi-round communication approach where agents coordinate via multiple rounds of communication before taking actions in the environment. We evaluate our approach on a diverse set of cooperative multi-agent tasks, of varying difficulties, with varying number of agents, in a variety of environments ranging from 2D grid layouts of shapes and simulated traffic junctions to 3D indoor environments, and demonstrate the benefits of targeted and multi-round communication. Moreover, we show that the targeted communication strategies learned by agents are interpretable and intuitive. Finally, we show that our architecture can be easily extended to mixed and competitive environments, leading to improved performance and sample complexity over recent state-of-the-art approaches.
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ICML - Tarmac: Targeted Multi-Agent Communication
2018Co-Authors: Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Michael G. Rabbat, Joelle PineauAbstract:We propose a targeted communication architecture for multi-agent reinforcement learning, where agents learn both what messages to send and whom to address them to while performing cooperative tasks in partially-observable environments. This targeting behavior is learnt solely from downstream task-specific reward without any communication supervision. We additionally augment this with a multi-round communication approach where agents coordinate via multiple rounds of communication before taking actions in the environment. We evaluate our approach on a diverse set of cooperative multi-agent tasks, of varying difficulties, with varying number of agents, in a variety of environments ranging from 2D grid layouts of shapes and simulated traffic junctions to 3D indoor environments, and demonstrate the benefits of targeted and multi-round communication. Moreover, we show that the targeted communication strategies learned by agents are interpretable and intuitive. Finally, we show that our architecture can be easily extended to mixed and competitive environments, leading to improved performance and sample complexity over recent state-of-the-art approaches.
James P. Phillips - One of the best experts on this subject based on the ideXlab platform.
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Preparation and response to a targeted automobile ramming mass casualty (Tarmac) attack: An analysis of the 2017 Charlottesville, Virginia Tarmac attack.
American journal of disaster medicine, 2019Co-Authors: James P. Phillips, Jeffrey S. Young, William J. BradyAbstract:Targeted automobile ramming mass casualty (Tarmac) attacks have recently become a common modality for those wishing to inflict mass harm. Intentional vehicular ramming is a unique wounding mechanism and deserves special consideration. An emergency response case analysis of the 2017 Tarmac attack in Charlottesville was conducted to review preparedness and identify shortcomings at the University of Virginia Health System University Hospital. Intentional mass blunt trauma is unique to Tarmac events, and current all-hazards approach preparedness may not suffice. Tarmac attacks warrant further attention by disaster medicine specialists; with adequate data, researchers may identify injury patterns and "lessons learned" that may improve mitigation strategies, provider preparation, and overall emergency care.
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The utility of point-of-care ultrasound in targeted automobile ramming mass casualty (Tarmac) attacks
The American journal of emergency medicine, 2018Co-Authors: Hamid Shokoohi, Ali Pourmand, Keith S. Boniface, Rebecca Allen, Bruno Petinaux, Babak Sarani, James P. PhillipsAbstract:As terrorist actors revise their tactics to outmaneuver increasing counter-terrorism security measures, a recent trend toward less-sophisticated attack methods has emerged. Most notable of these "low tech" trends are the Targeted Automobile Ramming MAss Casualty (Tarmac) attacks. Between 2014 and November 2017, 18 Tarmac attacks were reported worldwide, resulting in 181 deaths and 679 injuries. Tarmac attack-related injuries are unique compared to accidental pedestrian trauma and other causes of mass casualty incidents (MCI), and therefore they require special consideration. No other intentional mass casualty scenario is the result of a blunt, non-penetrating trauma mechanism. Direct vehicle impact results in high-power injuries including blunt trauma to the central nervous system (CNS), and thoracoabdominal organs with crush injuries if the victims are run over. Adopting new strategies and using existing technology to diagnose and treat MCI victims with these injury patterns will save lives and limit morbidity. Point-of-care ultrasound (POCUS) is one such technology, and its efficacy during MCI response is receiving an increasing amount of attention. Ultrasound machines are becoming increasingly available to emergency care providers and can be critically important during a MCI when access to other imaging modalities is limited by patient volume. By taking ultrasound diagnostic techniques validated for the detection of life-threatening cardiothoracic and abdominal injuries in individuals and applying them in a Tarmac mass casualty situation, physicians can improve triage and allocate resources more effectively. Here, we revisit the high-yield applications of POCUS as a means of enhanced prehospital and hospital-based triage, improved resource utilization, and identify their potential effectiveness during a Tarmac incident.
Abhishek Das - One of the best experts on this subject based on the ideXlab platform.
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Tarmac: Targeted Multi-Agent Communication
arXiv: Learning, 2018Co-Authors: Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Michael G. Rabbat, Joelle PineauAbstract:We propose a targeted communication architecture for multi-agent reinforcement learning, where agents learn both what messages to send and whom to address them to while performing cooperative tasks in partially-observable environments. This targeting behavior is learnt solely from downstream task-specific reward without any communication supervision. We additionally augment this with a multi-round communication approach where agents coordinate via multiple rounds of communication before taking actions in the environment. We evaluate our approach on a diverse set of cooperative multi-agent tasks, of varying difficulties, with varying number of agents, in a variety of environments ranging from 2D grid layouts of shapes and simulated traffic junctions to 3D indoor environments, and demonstrate the benefits of targeted and multi-round communication. Moreover, we show that the targeted communication strategies learned by agents are interpretable and intuitive. Finally, we show that our architecture can be easily extended to mixed and competitive environments, leading to improved performance and sample complexity over recent state-of-the-art approaches.
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ICML - Tarmac: Targeted Multi-Agent Communication
2018Co-Authors: Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Michael G. Rabbat, Joelle PineauAbstract:We propose a targeted communication architecture for multi-agent reinforcement learning, where agents learn both what messages to send and whom to address them to while performing cooperative tasks in partially-observable environments. This targeting behavior is learnt solely from downstream task-specific reward without any communication supervision. We additionally augment this with a multi-round communication approach where agents coordinate via multiple rounds of communication before taking actions in the environment. We evaluate our approach on a diverse set of cooperative multi-agent tasks, of varying difficulties, with varying number of agents, in a variety of environments ranging from 2D grid layouts of shapes and simulated traffic junctions to 3D indoor environments, and demonstrate the benefits of targeted and multi-round communication. Moreover, we show that the targeted communication strategies learned by agents are interpretable and intuitive. Finally, we show that our architecture can be easily extended to mixed and competitive environments, leading to improved performance and sample complexity over recent state-of-the-art approaches.
Cynthia Barnhart - One of the best experts on this subject based on the ideXlab platform.
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Tarmac Delay Policies: A Passenger-Centric Analysis
Transportation Research Part A: Policy and Practice, 2016Co-Authors: Chiwei Yan, Vikrant Vaze, Allison Elizabeth Vanderboll, Cynthia BarnhartAbstract:Abstract In this paper, we analyze the effectiveness of the 2010 Tarmac Delay Rule from a passenger-centric point of view. The Tarmac Delay Rule stipulates that aircraft lift-off, or an opportunity for passengers to deplane, must occur no later than 3 h after the cabin door closure at the gate of the departure airport; and that an opportunity for passengers to deplane must occur no later than 3 h after the touchdown at the arrival airport. The Tarmac Delay Rule aims to protect enplaned passengers on commercial aircraft from excessively long delays on the Tarmac upon taxi-out or taxi-in, and monetarily penalizes airlines that violate the stipulated 3-h Tarmac time limit. Comparing the actual flight schedule and delay data after the Tarmac Delay Rule was in effect with that before, we find that the Rule has been highly effective in reducing the frequency of occurrence of long Tarmac times. However, another significant effect of the rule has been the rise in flight cancellation rates. Cancellations result in passengers requiring rebooking, and often lead to extensive delay in reaching their final destinations. Using an algorithm to estimate passenger delay, we quantify delays to passengers in 2007, before the Tarmac Delay Rule was enacted, and compare these delays to those estimated for hypothetical scenarios with the Tarmac Delay Rule in effect for that same year. Our delay estimates are calculated using U.S. Department of Transportation data from 2007. Through our results and several sensitivity analyses, we show that the overall impact of the current Tarmac Delay Rule is a significant increase in passenger delays, especially for passengers scheduled to travel on the flights which are at risk of long Tarmac delays. We evaluate the impacts on passengers of a number of rule variations, including changes to the maximum time on the Tarmac, and variations in that maximum by time-of-day. Through extensive scenario analyses, we conclude that a better balance between the conflicting objectives of reducing the frequency of long Tarmac times and reducing total passenger delays can be achieved through a modified version of the existing rule. This modified version involves increasing the Tarmac time limit to 3.5 h and only applying the rule to flights with planned departure times before 5pm. Finally, in order to implement the Rule more effectively, we suggest the Tarmac time limit to be defined in terms of the time when the aircraft begin returning to the gate instead of being defined in terms of the time when passengers are allowed to deplane.
William J. Brady - One of the best experts on this subject based on the ideXlab platform.
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Preparation and response to a targeted automobile ramming mass casualty (Tarmac) attack: An analysis of the 2017 Charlottesville, Virginia Tarmac attack.
American journal of disaster medicine, 2019Co-Authors: James P. Phillips, Jeffrey S. Young, William J. BradyAbstract:Targeted automobile ramming mass casualty (Tarmac) attacks have recently become a common modality for those wishing to inflict mass harm. Intentional vehicular ramming is a unique wounding mechanism and deserves special consideration. An emergency response case analysis of the 2017 Tarmac attack in Charlottesville was conducted to review preparedness and identify shortcomings at the University of Virginia Health System University Hospital. Intentional mass blunt trauma is unique to Tarmac events, and current all-hazards approach preparedness may not suffice. Tarmac attacks warrant further attention by disaster medicine specialists; with adequate data, researchers may identify injury patterns and "lessons learned" that may improve mitigation strategies, provider preparation, and overall emergency care.
