20251230-KARL: Agents play the knowledge agreement game and adapt their knowledge base by selecting adaptation operators through Reinforcement Learning

This archive contains the results of a computational cultural knowledge evolution experiment [1,2]. Experiment design Agents are playing the knowledge-based agreement game using their symbolic knowledge base.Agents adapt their knowledge base by selecting operators through Reinforcement Learning. Hypotheses: [Learned policies are independent of the environment, Learned policies enable agents to reach consensus efficiently] Experimental Plan The independent variables have been varied as follows: LEARNING_METHOD = [random+, thompson, softmax, a3c] SEED = [24, 26, 27, 2626, 2727] (randomly selected) [1] https://sake.re/20251230-KARL[2] https://gitlab.inria.fr/moex/karlOperators