{'fraction_non_alphanumeric': 0.014623955431754874, 'fraction_numerical': 0.0, 'mean_word_length': 5.942028985507246, '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}}
Semi-Autonomous Navigation for Virtual Tactical Simulations in the Military Domain

Integrated constructive and virtual simulations are becoming popular for tactical training in the military domain. An important aspect concerning the integration of these simulation models in the construction of virtual tactical simulations is the modelling and implementation of different kinds of semi-autonomous agents. A fundamental feature of these agents is the capability of intelligently and realistically modelling task-oriented navigation activities in large virtual terrain simulation environments, while following underlying military doctrine and tactics. This paper reviews important navigation issues that emerge in such simulation systems and prominent Artificial Intelligence (AI) techniques that have been explored to solve them. From this analysis, a hybrid, semi-autonomous navigation framework is proposed aiming to fulfil the needs of virtual tactical training simulations, more specifically, in the military domain. As implemented in a system for the virtual tactical simulation of artillery battery tasks, the framework shows how to overcome the challenges of implementing realistic global and local navigation behaviours for military units and, at the same time, it shows that the semi-autonomous behaviours implemented are of primary importance to allow interaction with users for learning purposes in the simulation exercises.