{'fraction_non_alphanumeric': 0.016891891891891893, 'fraction_numerical': 0.0, 'mean_word_length': 5.26056338028169, '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}}
A Novel Algorithm of Cooperative Foraging for Swarm Robot Based on Neural Network*

Swarm robotics is an emerging discipline that has a great deal of potential real-world applications. Swarm robotics aims to produce robust, scalable, and flexible self-organizing behaviors through local interactions of large numbers of simple robots. In this paper, a novel pheromone model of swarm foraging behavior is developed based on a neural network. The output of the neurons corresponds to the density or pheromone. The output diffuses to the neighboring neurons through their local connections. The neural network is updated based on the proposed evaporation model. The evolution of the neural network can mimic the features of pheromones. Simulation experiments are performed under different foraging scenarios. The experimental results verify the effectiveness of the proposed pheromone model.