TY - GEN
T1 - Adapting stable matchings to evolving preferences
AU - Bredereck, Robert
AU - Chen, Jiehua
AU - Knop, Dušan
AU - Luo, Junjie
AU - Niedermeier, Rolf
N1 - Funding Information:
We thank anonymous reviewers of AAAI for their insightful comments. Main work was done while JC was with University of Warsaw, supported by ERC Horizon 2020 research and innovation programme (677651). JC was also supported by the WWTF research project (VRG18-012). Main work was done while DK was with TU Berlin, supported by the DFG project MaMu (NI 369/19). JL was supported by the DFG project AFFA (BR 5207/1 and NI 369/15).
Publisher Copyright:
Copyright © 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Adaptivity to changing environments and constraints is key to success in modern society. We address this by proposing “incrementalized versions” of STABLE MARRIAGE and STABLE ROOMMATES. That is, we try to answer the following question: for both problems, what is the computational cost of adapting an existing stable matching after some of the preferences of the agents have changed. While doing so, we also model the constraint that the new stable matching shall be not too different from the old one. After formalizing these incremental versions, we provide a fairly comprehensive picture of the computational complexity landscape of INCREMENTAL STABLE MARRIAGE and INCREMENTAL STABLE ROOMMATES. To this end, we exploit the parameters “degree of change” both in the input (difference between old and new preference profile) and in the output (difference between old and new stable matching). We obtain both hardness and tractability results, in particular showing a fixed-parameter tractability result with respect to the parameter “distance between old and new stable matching”.
AB - Adaptivity to changing environments and constraints is key to success in modern society. We address this by proposing “incrementalized versions” of STABLE MARRIAGE and STABLE ROOMMATES. That is, we try to answer the following question: for both problems, what is the computational cost of adapting an existing stable matching after some of the preferences of the agents have changed. While doing so, we also model the constraint that the new stable matching shall be not too different from the old one. After formalizing these incremental versions, we provide a fairly comprehensive picture of the computational complexity landscape of INCREMENTAL STABLE MARRIAGE and INCREMENTAL STABLE ROOMMATES. To this end, we exploit the parameters “degree of change” both in the input (difference between old and new preference profile) and in the output (difference between old and new stable matching). We obtain both hardness and tractability results, in particular showing a fixed-parameter tractability result with respect to the parameter “distance between old and new stable matching”.
UR - http://www.scopus.com/inward/record.url?scp=85090501935&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85090501935
T3 - AAAI 2020 - 34th AAAI Conference on Artificial Intelligence
SP - 1830
EP - 1837
BT - AAAI 2020 - 34th AAAI Conference on Artificial Intelligence
PB - AAAI press
T2 - 34th AAAI Conference on Artificial Intelligence, AAAI 2020
Y2 - 7 February 2020 through 12 February 2020
ER -