{'fraction_non_alphanumeric': 0.018312101910828025, 'fraction_numerical': 0.0, 'mean_word_length': 5.758064516129032, '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}}
Effects of strategy switching and network topology on decision-making in multi-agent systems

Abstract To study why the altruistic cooperation can emerge and maintain among self-interested individuals, researchers across several disciplines have made contributions for the solutions of this fascinating problem. Among this, a most-often used framework to describe cooperative dilemma is the evolutionary game theory. In traditional settings, an ideal hypothesis that individuals can feasibly obtain related partners' pay-offs for strategy updating is often adopted. However, considering the impracticality in acquiring accurate pay-offs of referential objects at each round of interaction, we propose switching probability which is independent of pay-offs and denotes the willingness of any individual shifts to another strategy. Here we provide results for the evolutionary dynamics driven by the switching probability in a three-strategy game model, played by the fully connected populations. The findings inform the befitting design of switching probabilities which maximally promote cooperation. We also derive general results that characterise the interaction of the three strategies: coexistence of multiple strategies or domination by some strategy.