{'fraction_non_alphanumeric': 0.016304347826086956, 'fraction_numerical': 0.0, 'mean_word_length': 5.538461538461538, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Automata Simulation of N-Person Social Dilemma Games

Collective behavior of N players in a social dilemma game is simulated by automata exhibiting cooperative behavior. In his models of simple biological systems, Tsetlin assumed minimum information available to the players. The automata in this study were somewhat more sophisticated, using Markov strategies in their interactions. The authors investigated relationships between information received by the automata and the emergence of cooperation in a simulated evolution process. In some ways, this approach is similar to that of Axelrod. However, instead of determining the most successful strategy, the authors seek surviving strategies in a social dilemma environment. Previous results showed that cooperation could be established asymptotically under partially centralized control. In this model there is no such control. The main result is that more sophisticated behavior of self-seeking automata compensates for the absence of such control. Moreover, cooperation is established more rapidly when more information is available to the automata.