TY - GEN
T1 - Tighter bounds for facility games
AU - Lu, Pinyan
AU - Wang, Yajun
AU - Zhou, Yuan
N1 - Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2009
Y1 - 2009
N2 - In one dimensional facility games, public facilities are placed based on the reported locations of the agents, where all the locations of agents and facilities are on a real line. The cost of an agent is measured by the distance from its location to the nearest facility. We study the approximation ratio of social welfare for strategy-proof mechanisms, where no agent can benefit by misreporting its location. In this paper, we use the total cost of agents as social welfare function. We study two extensions of the simplest version as in [9]: two facilities and multiple locations per agent. In both cases, we analyze randomized strategy-proof mechanisms, and give the first lower bound of 1.045 and 1.33, respectively. The latter lower bound is obtained by solving a related linear programming problem, and we believe that this new technique of proving lower bounds for randomized mechanisms may find applications in other problems and is of independent interest. We also improve several approximation bounds in [9], and confirm a conjecture in [9].
AB - In one dimensional facility games, public facilities are placed based on the reported locations of the agents, where all the locations of agents and facilities are on a real line. The cost of an agent is measured by the distance from its location to the nearest facility. We study the approximation ratio of social welfare for strategy-proof mechanisms, where no agent can benefit by misreporting its location. In this paper, we use the total cost of agents as social welfare function. We study two extensions of the simplest version as in [9]: two facilities and multiple locations per agent. In both cases, we analyze randomized strategy-proof mechanisms, and give the first lower bound of 1.045 and 1.33, respectively. The latter lower bound is obtained by solving a related linear programming problem, and we believe that this new technique of proving lower bounds for randomized mechanisms may find applications in other problems and is of independent interest. We also improve several approximation bounds in [9], and confirm a conjecture in [9].
UR - http://www.scopus.com/inward/record.url?scp=76749093740&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=76749093740&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-10841-9_14
DO - 10.1007/978-3-642-10841-9_14
M3 - Conference contribution
AN - SCOPUS:76749093740
SN - 3642108407
SN - 9783642108402
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 137
EP - 148
BT - Internet and Network Economics - 5th International Workshop, WINE 2009, Proceedings
T2 - 5th International Workshop on Internet and Network Economics, WINE 2009
Y2 - 14 December 2009 through 18 December 2009
ER -