Payoffs and perception mediate environmental feedback in an N-player trust game with Q-learning
Abstract
Trust develops through learning, while collective behavior can alter the environment in which later decisions are made. Reinforcement-learning models describe adaptation, and eco-evolutionary models describe behavior-environment feedback, but how an endogenous environment changes trust through material incentives and perceived states remains unclear. We couple a fixed-role, two-population hierarchical trust game populated by heterogeneous tabular Q-learning agents to a centered endogenous environment. For the main feedback comparisons, we initialize the fixed-payoff baseline and feedback branches from the same learned state to control for prior learning. We then compare responses when payoff parameters or the observed environmental tier vary. As the payoff multiplication factor increased, successful trust in the fixed-payoff game crossed from a low to a higher finite-horizon level, led by risk-seeking investors. Environmental feedback promoted trust near perception-tier boundaries and reinforced its decline at the high-return operating point. At the high-return operating point, payoff feedback reinforced the learning-driven decline in trust. Stronger drive and longer horizons deepened this negative effect. Compared with a fixed-payoff trust game, environmental feedback carries past collective outcomes into future payoffs and observed states.
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BibTeX
@misc{guo2026payoffs,
title = {{Payoffs and perception mediate environmental feedback in an N-player trust game with Q-learning}},
author = {Ruqiang Guo and Zhaoyi Hu and Fangfang Wang and Linjie Liu},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.24493},
eprint = {2609.24493},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.24493},
}
RIS
TY - UNPB
TI - Payoffs and perception mediate environmental feedback in an N-player trust game with Q-learning
AU - Ruqiang Guo
AU - Zhaoyi Hu
AU - Fangfang Wang
AU - Linjie Liu
PY - 2026
DA - 2026/09/21
PB - arXiv
DO - 10.48550/arxiv.2609.24493
UR - https://arxiv.org/abs/2609.24493
AB - Trust develops through learning, while collective behavior can alter the environment in which later decisions are made. Reinforcement-learning models describe adaptation, and eco-evolutionary models describe behavior-environment feedback, but how an endogenous environment changes trust through material incentives and perceived states remains unclear. We couple a fixed-role, two-population hierarchical trust game populated by heterogeneous tabular Q-learning agents to a centered endogenous environment. For the main feedback comparisons, we initialize the fixed-payoff baseline and feedback branches from the same learned state to control for prior learning. We then compare responses when payoff parameters or the observed environmental tier vary. As the payoff multiplication factor increased, successful trust in the fixed-payoff game crossed from a low to a higher finite-horizon level, led by risk-seeking investors. Environmental feedback promoted trust near perception-tier boundaries and reinforced its decline at the high-return operating point. At the high-return operating point, payoff feedback reinforced the learning-driven decline in trust. Stronger drive and longer horizons deepened this negative effect. Compared with a fixed-payoff trust game, environmental feedback carries past collective outcomes into future payoffs and observed states.
ER -