{'fraction_non_alphanumeric': 0.017427385892116183, 'fraction_numerical': 0.0008298755186721991, 'mean_word_length': 5.03, '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 cloud service for robotic mental simulations

Robotic agents that do everyday manipulation tasks can hugely benefit from being able to predict consequences of their actions just before the execution. However, such a simulation technique is usually computationally-expensive and may not be achieved with agents' self computing power. For this problem, cloud robotics may offer a solution. Cloud robotics is an emerging field in the intersection of robotics and cloud computing which enables robots to access a greater amount of processing power and storage capacity than it can employ within itself. In this work, we introduce a mental simulation service to, one of the cloud engines, openEASE [1]. Using this service, researchers and robots can describe the world model, the state of the agent and the problem that is being dealt with. In return, it simulates the world and runs a learning algorithm and suggests a solution how the robotic agent can handle the problem. This service does not only offer a free remote access to simulation which is computationally expensive but also thanks to OPEnEASE's rich reasoning techniques these simulated experiments can be reasoned later on using prolog queries.