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Deliberation-aware Responder in Multi-Proposer Ultimatum Game
- 1.0462891 - ÚTIA 2017 RIV CH eng C - Conference Paper (international conference)
Ruman, Marko - Hůla, František - Kárný, Miroslav - Guy, Tatiana Valentine
Deliberation-aware Responder in Multi-Proposer Ultimatum Game.
Artificial Neural Networks and Machine Learning – ICANN 2016. Vol. Part I. Cham: Springer, 2016, s. 230-237. Lecture Notes in Computer Science, 9886. ISBN 978-3-319-44777-3. ISSN 0302-9743.
[International Conference on Artificial Neural Networks 2016 /25./. Barcelona (ES), 06.09.2016-09.09.2016]
R&D Projects: GA AV ČR GA16-09848S
Institutional support: RVO:67985556
Keywords : deliberation effort * Markov decision process * ultimatum game
Subject RIV: BB - Applied Statistics, Operational Research
http://library.utia.cas.cz/separaty/2016/AS/karny-0462891.pdf
The article studies deliberation aspects by modelling a responder in multi-proposers ultimatum game (UG). Compared to the classical UG, deliberative multi-proposers UG suggests that at each round the responder selects the proposer to play with. Any change of the proposer (compared to the previous round) is penalised. The simulation results show that though switching of proposers incurred non-negligible deliberation costs, the economic profit of the deliberation-aware responder was significantly higher in multi-proposer UG compared to the classical UG.
Permanent Link: http://hdl.handle.net/11104/0262367
Number of the records: 1