Mar 1, 2021 · Using these, we show that our deep reinforcement learning agent can learn winning strategies for Monopoly against different fixed-policy agents.
Sep 14, 2023 · In this paper, we present novel representations for the state and action space for the full version of Monopoly and define an improved reward ...
Feb 1, 2024 · The hybrid deep reinforcement learning model is designed to process and interpret the intricate game state representations, learning optimal ...
This paper presents novel representations for the state and action space for the full version of Monopoly and defines an improved reward function.
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Decision Making in Monopoly Using a Hybrid Deep Reinforcement Learning Approach ... Authors: Trevor Bonjour; Marina Haliem; Aala Alsalem; Shilpa Thomas; Hongyu Li ...
Decision Making in Monopoly Using a Hybrid Deep Reinforcement Learning Approach. Bonjour, T., Haliem, M., Alsalem, A. O., Thomas, S., Li, H., Aggarwal, V., ...
Learning monopoly gameplay: A hybrid model-free deep reinforcement learning and imitation learning approach
Sep 10, 2024 · This research introduces a novel approach to decision-making in the classic board game Monopoly by leveraging a hybrid deep reinforcement ...
Decision Making in Monopoly Using a Hybrid Deep Reinforcement Learning Approach · Computer Science, Economics. IEEE Transactions on Emerging Topics in… · 2022.
Mar 1, 2021 · This makes the decision-making harder and thus, introduces a highly complicated task for an RL agent to play and learn its winning strategies.