Publication details
Conference Paper (international conference)
Deliberation-aware Responder in Multi-Proposer Ultimatum Game
, , ,
: Artificial Neural Networks and Machine Learning – ICANN 2016, p. 230-237
: International Conference on Artificial Neural Networks 2016 /25./, (Barcelona, ES, 20160906)
: GA16-09848S, GA AV ČR
: deliberation effort, Markov decision process, ultimatum game
: 10.1007/978-3-319-44778-0_27
: http://library.utia.cas.cz/separaty/2016/AS/karny-0462891.pdf
(eng): 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.
: BB