Decision Support for Agent Populations in Uncertain and Congested Environments

This research is motivated by large scale problems in urban transportation and labor mobility where there is congestion for resources and uncertainty in movement. In such domains, even though the individual agents do not have an identity of their own and do not explicitly interact with other agents,...

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Main Authors: VARAKANTHAM, Pradeep Reddy, CHENG, Shih-Fen, GORDON, Geoff, AHMED, Asrar
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Language:English
Published: Institutional Knowledge at Singapore Management University 2012
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Online Access:https://ink.library.smu.edu.sg/sis_research/1567
https://ink.library.smu.edu.sg/context/sis_research/article/2566/viewcontent/AAAI12_226.pdf
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spelling sg-smu-ink.sis_research-25662015-12-05T13:01:41Z Decision Support for Agent Populations in Uncertain and Congested Environments VARAKANTHAM, Pradeep Reddy CHENG, Shih-Fen GORDON, Geoff AHMED, Asrar This research is motivated by large scale problems in urban transportation and labor mobility where there is congestion for resources and uncertainty in movement. In such domains, even though the individual agents do not have an identity of their own and do not explicitly interact with other agents, they effect other agents. While there has been much research in handling such implicit effects, it has primarily assumed deterministic movements of agents. We address the issue of decision support for individual agents that are identical and have involuntary movements in dynamic environments. For instance, in a taxi fleet serving a city, when a taxi is hired by a customer, its movements are uncontrolled and depend on (a) the customers requirement; and (b) the location of other taxis in the fleet. Towards addressing decision support in such problems, we make two key contributions: (a) A framework to represent the decision problem for selfish individuals in a dynamic population, where there is transitional uncertainty (involuntary movements); and (b) Two techniques (Fictitious Play for Symmetric Agent Populations, FP-SAP and Softmax based Flow Update, SMFU) that converge to equilibrium solutions.We show that our techniques (apart from providing equilibrium strategies) outperform “driver” strategies with respect to overall availability of taxis and the revenue obtained by the taxi drivers. We demonstrate this on a real world data set with 8,000 taxis and 83 zones (representing the entire area of Singapore). 2012-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1567 https://ink.library.smu.edu.sg/context/sis_research/article/2566/viewcontent/AAAI12_226.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Artificial Intelligence and Robotics Business Operations Research, Systems Engineering and Industrial Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Artificial Intelligence and Robotics
Business
Operations Research, Systems Engineering and Industrial Engineering
spellingShingle Artificial Intelligence and Robotics
Business
Operations Research, Systems Engineering and Industrial Engineering
VARAKANTHAM, Pradeep Reddy
CHENG, Shih-Fen
GORDON, Geoff
AHMED, Asrar
Decision Support for Agent Populations in Uncertain and Congested Environments
description This research is motivated by large scale problems in urban transportation and labor mobility where there is congestion for resources and uncertainty in movement. In such domains, even though the individual agents do not have an identity of their own and do not explicitly interact with other agents, they effect other agents. While there has been much research in handling such implicit effects, it has primarily assumed deterministic movements of agents. We address the issue of decision support for individual agents that are identical and have involuntary movements in dynamic environments. For instance, in a taxi fleet serving a city, when a taxi is hired by a customer, its movements are uncontrolled and depend on (a) the customers requirement; and (b) the location of other taxis in the fleet. Towards addressing decision support in such problems, we make two key contributions: (a) A framework to represent the decision problem for selfish individuals in a dynamic population, where there is transitional uncertainty (involuntary movements); and (b) Two techniques (Fictitious Play for Symmetric Agent Populations, FP-SAP and Softmax based Flow Update, SMFU) that converge to equilibrium solutions.We show that our techniques (apart from providing equilibrium strategies) outperform “driver” strategies with respect to overall availability of taxis and the revenue obtained by the taxi drivers. We demonstrate this on a real world data set with 8,000 taxis and 83 zones (representing the entire area of Singapore).
format text
author VARAKANTHAM, Pradeep Reddy
CHENG, Shih-Fen
GORDON, Geoff
AHMED, Asrar
author_facet VARAKANTHAM, Pradeep Reddy
CHENG, Shih-Fen
GORDON, Geoff
AHMED, Asrar
author_sort VARAKANTHAM, Pradeep Reddy
title Decision Support for Agent Populations in Uncertain and Congested Environments
title_short Decision Support for Agent Populations in Uncertain and Congested Environments
title_full Decision Support for Agent Populations in Uncertain and Congested Environments
title_fullStr Decision Support for Agent Populations in Uncertain and Congested Environments
title_full_unstemmed Decision Support for Agent Populations in Uncertain and Congested Environments
title_sort decision support for agent populations in uncertain and congested environments
publisher Institutional Knowledge at Singapore Management University
publishDate 2012
url https://ink.library.smu.edu.sg/sis_research/1567
https://ink.library.smu.edu.sg/context/sis_research/article/2566/viewcontent/AAAI12_226.pdf
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