1	Introduction to Advanced AI Topics Vision Natural Language Processing Robotics
2	Homework #2 We are not yet ready to hand out Homework #2. We will probably have it ready for you by Friday. You will be grouping yourselves into teams of three students via a web form. We will announce the URL for this on Friday.
3	Advanced Topics Overview Agents have sensors and actuators Sensors: Seeing (visual input) Þ Image Processing and Computer Vision Hearing (audio input) Þ Natural Language Processing Actuators: Moving and manipulating Þ Robotics
4	Computer Vision Perception
5	Definition: versus graphics Graphics Have world model W Generate the sensory stimulus from the model S = f(W) Vision Generate the model from the sensors: W = f^-1(S) To think about: f() doesn’t have a proper inverse. Why?
6	Ambiguity in sensory input Girls playing with dollhouses Or giants playing with people?
7	Definition: versus image processing Image Processing A transformation of data to other data e.g., smoothing Computer Vision Reduction in data to a (more useful) abstraction e.g., digit / face recognition
8	Applications Surveillance – can we detect objects or people as they move around our field of vision? Handwriting recognition – from handwritten addresses to barcodes Content based Image Retrieval – query for images using without any text features. “Show me similar pictures” Automated Driving – speaks for itself
9	Natural Language Processing Communication
10	Definition of NLP Examines communication in human languages. Theoretical and practical aspects. Similar to vision, has production and understanding affects Understanding: speech / text to meaning Generation: meaning to speech / text Both processes have inherent ambiguity
11	Not so great newspaper headlines Squad helps dog bite victim. Helicopter powered by human flies Portable toilet bombed; police have nothing to go on. British left waffles on Falkland Islands. Teacher strikes idle kids.
12	Sample Applications Restaurant Query converts English queries into SQL. MS Dictation converts speech into text Babelfish translates Web pages to different languages Summarizing multiple news articles from the web
13	Robotics Planning in the real world environment
14	Getting around Effectors Sensors on effectors? Is the output noisy? Low-level: need to build higher-level abstractions
15	Problems Localization – where am I? Mobile robots but also robotic arms Mapping – what does my environment look like? Moving – how do I get from here to my goal? What type of plan do I have execute?
16	Applications of robotics Robotic Flight – robotic helicopter, unmanned piloting Path planning for exploration Rock climbing, perhaps difficult even for some of us
17	Summary All three areas deal with search: Vision: search for most likely world w given input sensor s Natural Language Processing: given an input utterance / text i, find most likely meaning m Robotics: Localization: given unknown input configuration / location, determine configuration. Planning: given goal g and state s output plan p to reach g from s
18	Summary All three areas use heuristics : Vision: trihedral structure Natural Language Processing: grammars of language, most frequent meanings Robotics: decomposition of problems into cells, maximizing distance between obstacles Many of these heuristics involve probability, which we will return to at the end of the semester.