辅导COMP9418课程、写作program编程设计、Python

” 辅导COMP9418课程、写作program编程设计、PythonAssignment 2COMP9418 Advanced Topics in Statistical Machine LearningLast revision: Monday 2nd November, 2020 at 19:11Assignment designed by Jeremy GillenInstructionsSubmission deadline: Sunday, 22nd November 2020, at 18:00:00.Late Submission Policy: The penalty is set at 20% per late day. This is a ceiling penalty, so if a group ismarked 60/100 and they submitted two days late, they still get 60/100.Form of Submission: This is a group assignment. Each group can have up to two students. Write thenames and zIDs of each student at the top of solution.py and in your report. Only one member of thegroup should submit the assignment.There is a maximum file size cap of 5MB, so make sure your submission files do not in total exceed this size.You are allowed to use any Python library used in the tutorial notebooks or given in the example code.No other library will be accepted, particularly libraries for graph and Bayesian network representation andoperation. Also, you can reuse any piece of source code developed in the tutorials.Submit Your files using give. On a CSE Linux machine, type the following on the command-line:$ give cs9418 ass2 solution.py report.pdf *.csv *.pyZero or more csv files can be submitted to store the parameters of your model, to be loaded by solution.pyduring testing. Zero or more python helper files may be included in the submission, if you want to organiseyour code using multiple files.Alternatively, you can submit your solution via WebCMS.Recall the guidance regarding plagiarism in the course introduction: this applies to this assignment, and ifevidence of plagiarism is detected, it will result in penalties ranging from loss of marks to suspension.ChangelogOct 30th: Added clarification that the cost is calculated using instantaneous counts of people in each room(i.e. every 15 seconds, a snapshot of each room is magically taken at exactly the same time, and the numberof people in each room is counted. If someone passes through multiple rooms within 15 seconds, they willnot increment the count in multiple rooms, only in one room). Added clarification that the ground truthnumber of people in each room is also an instantaneous value. Added clarification that sensor data is notinstantaneous, but robot reports are.Nov 2nd: Added additional information: the number of people who come to the office each day variesaccording to this distribution: num_people = round(Normal(mean=20, stddev=1)). This information wasobtained from records of the number of workers present each day.1DescriptionIn this assignment, you will write a program that plays the part of a smart building. This program will begiven a real-time stream of sensor data from throughout the building, and use this data to decide whetherto turn on the lights in each room. Your goal is to minimise the cost of lighting in the building, while alsotrying to make sure that The lights stay on if there are people in a room. Every 15 seconds, you will receive anew data point and have to decide whether each light should be turned on or off. There are several typesof sensors in the building, each with different reliability and data output. You will be given a file calleddata.csv containing one day of complete data with all sensor values and the number of people in each room.This assignment can be approached in many different ways. We will not be giving any guidance on whatalgorithms are most appropriate.Your solution must include a Probabilistic Graphical Model as the core component. Other than that you arefree to use any algorithm as part of your approach, including any algorithm available in Pythons sklearnlibrary.It is recommended you Start this assignment by discussing several different possible approaches with yourpartner. Make sure you discuss what information you have available, what information is uncertain, andwhat assumptions it May be reasonable to make.Every area on the floor plan is named with a string of the form r, c, o, or outside. r,c and o standfor room, corridor, and open area respectively.DataThe file data.csv contains complete data that is representative of a typical weekday in the office building.This data includes the output of each sensor as well as the true number of people in each room. This datawas generated using a simulation of the building, and your program will be tested against many days of datagenerated by the same simulation. Because this data would be expensive to collect, you are only given 2400complete data points, from a single workday. The simulation attempts to be a realistic approximation toreality, so it includes many different types of noise and bias. You should treat this project as if the data camefrom a real office building, and is to be tested on real data from that building. You can make any assumptionsthat you think would be reasonable in the real world, and you should describe all assumptions in the report.Part of your mark will be Determined by the feasibility of your assumptions, if applied to the real world.Added Nov 2nd: [** The number of people who come to the office each day varies according tothis distribution: num_people = round(Normal(mean=20, stddev=1)). This information wasobtained from records of the number of workers present each day, and the empirical distributionof num_people was Found to be identical to round(Normal(mean=20, stddev=1)).**]Data format specificationSensor dataYour submission file must contain a function called get_action(sensor_data), which receives sensor datain the following format:sensor_data = {reliable_sensor1: motion, reliable_sensor2: motion,reliable_sensor3: motion, reliable_sensor4: motion,unreliable_sensor1: motion, unreliable_sensor2: motion,unreliable_sensor3: motion, unreliable_sensor4: motion,door_sensor1: 0, door_sensor2: 0, door_sensor3: 0, door_sensor4:0,robot1: (r1, 0), robot2: (r16, 0), time: datetime.time(8, 0), electricity_price: 0.81}Added Oct 30th: [The motion and door sensors report on motion from the entire previous 15seconds, but the robot reports an instantaneous count of the number of people.]2The possible values of each field in sensor_data are: reliable_sensors and unreliable_sensors can have the values [motion, no motion]. All reliable_sensorsare of the same brand and are usually quite accurate. unreliable_sensors are a different type of motionsensor, which you know tends to be a little less accurate. door_sensors count how many people passed through a door (in either direction), so it can be anyinteger. The robot sensors are robots that wander around the building and count the number of people in eachroom. The value is a 2-tuple of the current room, and the number of people counted. I.e. if the robotgoes into r4 and Counts 8 people, it would have the value (r4,8). If it goes into room c2 and no one ispresent, it would have value (c2,0). Any of the sensors may fail at any time, in which case they will have the value None. They may startworking again.The value of time is a datetime.time object representing the current time. Datapoints will be provided in 15second resolution, i.e., your function will be fed data points from 15 second intervals from 8 am – 6 pm.Training dataThe file data.csv contains a column for each of the above sensors, as well as columns for each room, whichtell you the current number of people in that room. The columns of data.csv are the following and can bedivided into two groups:1. Columns that represent readings from sensors, as described in the previous section: reliable_sensor1,reliable_sensor2, reliable_sensor3, reliable_sensor4, unreliable_sensor1, unreliable_sensor2, unreliable_sensor3,unreliable_sensor4, robot1, robot2, door_sensor1, door_sensor2, door_sensor3,door_sensor4, time, electricity_price.2. Columns that are present only in the training data and provide the ground truth with the numberof people in each room, corridor, open area, and outside the building: r1, r2, r3, r4, r5, r6, r7, r8,r9, r10, r11, r12, r13, r14, r15, r16, r17, r18, r19, r20, r21, r22, r23, r24, r25, r26, r27, r28, r29, r30,r31, r32, r33, r34, r35, c1, c2, c3, c4, o1, outside. Added Oct 30th: [This ground truth dataprovides the instantaneous count of people per room (i.e. Every 15 seconds, a snapshotof each room is magically taken at exactly the same time, and the number of people ineach room is counted. If someone passes through multiple rooms within 15 seconds, theywill not increment the count in multiple rooms, only in one room) ].Note that the first Column of data.csv is the index, and has no name.You should use this data to learn the parameters of your model. Also, you can save the parameters to csvfiles that can be loaded during testing.Action dataget_action() must return a dictionary with the following format. Note that every numbered room namedr in the building has lights that you can turn on or off. All other rooms/corridors have lights that arepermanently on, which you have no control over, and which do not affect the cost.actions_dict = {lights1: off, lights2: off, lights3: off,lights4: off, lights5: off, lights6: off, lights7: off,lights8: off, lights9: off, lights10: off, lights11: off,lights12: off, lights13: off, lights14: off, lights15: off,lights16: off, lights17: off,lights18: off, lights19: off,lights20: off, lights21: off, lights22: off, lights23: off,lights24: off, lights25: off, lights26: off, lights27: off,lights28: off, lights29: off,lights30: off, lights31: off,lights32: off, lights33: off, lights34: off,lights35: off}3The outcome space of all actions is (on,off).In the provided example_solution.py, there is an example code stub that shows an example of how to setup your code.Figure 1 shows the floor plan specification.Cost specificationIf a light is on in a room for 15 seconds, it usually costs you about 1 cent. The exact price of electricity goesup and down, but luckily, the electricity provider lists the current price online, and this price is includedin the sensor_data. If there are people in a room and there is no light on, it costs you 4 cents per personevery 15 seconds, because of lost productivity. Added Oct 30: [The cost can be calculated exactlyusing the complete training data, so it is also based on an instantaneous count of the numberof people in each room.]Your goal is to minimise the total cost of lighting plus lost productivity, added up over the whole day. You donot need to Calculate this cost, the testing code will calculate it using the actions returned by your function,and the true locations of people (unavailable to you). The file example_test.py shows exactly how the costis calculated.Testing specificationYour program must be submitted as a python file called solution.py. During testing, solution.py will beplaced in a folder with test.py. A simpler version of test.py has been provided (called example_test.py),so you can confirm that testing will work. A more elaborate version of test.py will be used to grade yoursolution.ReportYour report should cover the following points: What algorithms you used, a brief description of how they work, and their time complexity. A short justification of the methods you used (if you tried different variations, describe them). Any assumptions you made when creating your model.The report must be less than 2000 words (around 4 pages of text). The only accepted format is PDF.Marking CriteriaThis assignment will be marked according to the following criteria:1. 50% of the mark will be determined by the cost incurred by your code after several days of simulateddata. The Mapping from cost to marks will be determined after the assignment has been submitted.2. 20% of the mark will be determined by the description of the algorithms used, and a short justificationof the methods used.3. 10% of the mark Will be determined by a description of the assumptions and/or simplifications youmade in your model, and whether those assumptions would be effective in the real-world.4. 20% of the mark will be determined by the quality, readability and efficiency of the code.Items 2 and 3 will be Assessed using the report. Items 1 and 4 will be assessed using python file.4Figure 1: Floor plan (note that dotted grey lines denote the boundaries of areas when the boundary isunclear).5Bonus MarksBonus marks will be Given to the top 10 performing programs (10 percentage points for 1st place, 1 percentagepoint for 10th place).如有需要，请加QQ：99515681 或邮箱：99515681@qq.com

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