You may use figures and illustrations as part of your solutions. You may insert additional pages to write your solutions as necessary. Please also include the name and/or web links to your reference sources. you are provided an opportunity to explore variations of methods that have been discussed in class and/or use Artificial Intelligence to solve real-world problems in the following domains: 1) Search and Heuristics: Robotics and Games 2) Markov Decision Processes and Reinforcement Learning Please Use REAL WORLD examples and describe the algorithms that can be used in the context of your selected problems and real-world scenarios. 1) Machine Learning and Knowledge Representation (100 points) Knowledge representation can help to enable an intelligent machine to learn from knowledge and experience so that it can behave intelligently like a human. Describe and design a real-world application or scenario where you would use machine learning representations to represent and process knowledge. a) Explain your rationale behind any machine learning methodology you have selected, and how it may be effective towards addressing your real-world scenario. b) Describe any challenges that may be encountered as well. c) Evaluate alternate approaches you could try, and discuss why they may or may not be appropriate for representing knowledge through a machine learning system. 2) Deep Learning for Natural Language Processing and Computer Vision (100 points) a) Natural Language Processing (50 points) The goal of using Natural language processing (NLP) technologies is to build systems that learn to understand and represent human language and use language in appropriate context. Describe and design a deep learning-based model which can help perform text analysis and understanding. You may use any real-life example where natural language processing is used to understand human language. Examples may include question answering, natural language inference, semantic word embeddings, and syntactic parsing. b) Computer Vision (50 points) Deep learning has helped bring many new applications using computer vision techniques into our daily lives. Describe and design a deep learning-based model which can help perform computer vision analysis. You may use any real-life example where computer vision is used to understand to learning meaning from images and objects. Examples may include image classification, image transformation, object detection, segmentation, medical image analysis, etc.