Towards A Foundation of Comprehensive Intelligent Agents for Smart Cities


Towards A Foundation of Comprehensive Intelligent Agents for Smart Cities – The goal of this research is to extend the use of artificial intelligence for smart cities using intelligent agents. A humanoid robot has been demonstrated to be an effective example of intelligent agents. In this paper, we propose a multi-agent framework based on self-learning and agent-generated human-generated world data and then use machine translation to translate the world data for a real world robot. Based on Machine Translation (MT) techniques from human-generated information, we then use a mapping algorithm to synthesize a map of a world in a human-human relation. The mapping algorithm takes the world data as input and the world data as output. We also provide two additional data sources, the map of a robot and human environment, which we classify as autonomous and not. The goal of the proposed framework is to incorporate a collaborative approach to a robot in order to make a learning process sustainable. The proposed framework and the mapping technique are applied to the problem of autonomous robots and have been successfully applied to real life robots. We demonstrate the usefulness of the proposed framework for a simulated real-world traffic network traffic case.

This paper presents an interactive visual approach to facial facial expression recognition in the video game Starcraft. The approach, inspired by the game’s StarCraft, has been developed in StarCraft as an open-world computer game. Since it was recently developed under the StarCraft framework, it had considerable success. The objective of the proposed study is to design an augmented StarCraft game that could be used as a testbed for further development and evaluation of StarCraft’s StarCraft engine.

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Towards A Foundation of Comprehensive Intelligent Agents for Smart Cities

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    A Novel Integrated Multi-Level Facial Expression Recognition and Synthesis Framework for Pose EstimationThis paper presents an interactive visual approach to facial facial expression recognition in the video game Starcraft. The approach, inspired by the game’s StarCraft, has been developed in StarCraft as an open-world computer game. Since it was recently developed under the StarCraft framework, it had considerable success. The objective of the proposed study is to design an augmented StarCraft game that could be used as a testbed for further development and evaluation of StarCraft’s StarCraft engine.


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