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Benny Lutati

dblp:149/1338 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Algorithmic game theory and mechanism design · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Energy systems and smart grids · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design
congestion games
0.212014
Congestion Games for V2G-Enabled EV Charging · AAAI 2014
Algorithmic game theory and mechanism design › solution concepts in games › equilibrium concepts
nash equilibrium
0.212014
Congestion Games for V2G-Enabled EV Charging · AAAI 2014
Algorithmic game theory and mechanism design › non-cooperative game
potential game
0.212014
Congestion Games for V2G-Enabled EV Charging · AAAI 2014
Energy systems and smart grids
electric vehicle charging
0.112014
Congestion Games for V2G-Enabled EV Charging · AAAI 2014
Energy systems and smart grids › electric vehicle charging
vehicle-to-grid
0.112014
Congestion Games for V2G-Enabled EV Charging · AAAI 2014

Methods — techniques the papers use, named apart from their topics

best-response dynamics · 0.2best response dynamics · 0.2
YearPublicationVenuePosition
2014 Congestion Games for V2G-Enabled EV Charging
abstract
A model of the problem of charging and discharging electrical vehicles as a congestion game is presented. A generalization of congestion games - feedback congestion games (FCG) - is introduced. The charging of grid-integrated vehicles, which can also discharge energy back to the grid, is a natural FCG application. FCGs are proven to be exact potential games and therefore converge to a pure-strategy Nash equilibrium by an iterated better-response process. A compact representation and an algorithm that enable efficient best-response search are presented. A detailed empirical evaluation assesses the performance of the iterated best-response process. The evaluation considers the quality of the resulting solutions and the rate of convergence to a stable state. The effect of allowing to also discharge batteries using FCG is compared to scenarios that only include charging and is found to dramatically improve the predictability of the achieved solutions as well as the balancing of load.
Benny Lutati, Vadim Levit 0001, Tal Grinshpoun, Amnon Meisels
AAAI1