TY - GEN
T1 - "Reverse Gerrymandering"
T2 - 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019
AU - Lev, Omer
AU - Lewenberg, Yoad
N1 - Funding Information:
This research has been partially supported by the HUJI Cy-ber Security Research Center in conjunction with the Israel National Cyber Directorate (INCD) in the Prime Minister’s Office.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - District-based manipulation, or gerrymandering, is usually taken to refer to agents who are in fixed location, and an external division is imposed upon them. However, in many real-world setting, there is an external, fixed division - an organizational chart of a company, or markets for a particular product. In these cases, agents may wish to move around (“reverse gerrymandering”), as each of them tries to maximize their influence across the company's subunits, or resources are “working” to be allocated to areas where they will be most needed. In this paper we explore an iterative dynamic in this setting, finding that allowing this decentralized system results, in some particular cases, in a stable equilibrium, though in general, the setting may end up in a cycle. We further examine how this decentralized process affects the social welfare of the system.
AB - District-based manipulation, or gerrymandering, is usually taken to refer to agents who are in fixed location, and an external division is imposed upon them. However, in many real-world setting, there is an external, fixed division - an organizational chart of a company, or markets for a particular product. In these cases, agents may wish to move around (“reverse gerrymandering”), as each of them tries to maximize their influence across the company's subunits, or resources are “working” to be allocated to areas where they will be most needed. In this paper we explore an iterative dynamic in this setting, finding that allowing this decentralized system results, in some particular cases, in a stable equilibrium, though in general, the setting may end up in a cycle. We further examine how this decentralized process affects the social welfare of the system.
UR - http://www.scopus.com/inward/record.url?scp=85090800058&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85090800058
T3 - 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019
SP - 2069
EP - 2076
BT - 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019
PB - AAAI press
Y2 - 27 January 2019 through 1 February 2019
ER -