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The paper presents an evolutionary model, based on the assumption that agents may revise their current strategies if they previously failed to attain the maximum level of potential payoffs. We offer three versions of this reflexive mechanism, each one of which describes a distinct type:...
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affiliation-motivated individuals engaged in game-play. The first model captures learning by motivated agents during strategic …
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opportunities to identify learning rules, since on networks (compared to, e.g., random matching) more rules differ in terms of their … information they consult before making their choices. We use these data to estimate learning types using finite mixture models … find that learning depends on network position. Participants in more complex environments (with more network neighbors …
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This study explores the dynamics of international strategic learning alliances through the lens of game theory … findings offer valuable guidance for international partners involved in learning alliances, emphasizing the importance of … to the discourse on inter-firm cooperation by highlighting the complexities of strategic learning alliances and offering …
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