Simulated trust: a cheap social learning strategy.

Area of Science:

• Behavioral Ecology
• Evolutionary Game Theory
• Animal Cognition

Background:

• Animals employ heuristic strategies for directed social learning to avoid maladaptive information.
• Current models often assume social learning strategies depend on inferring demonstrator success.

Purpose of the Study:

• To propose and evaluate an alternative social learning strategy based on self-assessed behavioral payoffs.
• To investigate the role of incremental learning in the success of such strategies.

Main Methods:

• Agent-based simulations were used to model and test the proposed social learning strategy.
• The strategy's efficacy was analyzed with a focus on an included incremental learning mechanism.

Main Results:

• The proposed strategy, utilizing self-established payoff estimates, proved effective in simulations.
• The inclusion of an incremental learning mechanism was critical for the strategy's success.

Conclusions:

• This study presents a novel framework for directed social learning in animals, relying on direct payoff evaluation.
• Findings suggest a need to incorporate realistic learning mechanisms into game-theoretic models of social learning and re-evaluate prior research.