R编程设计调试、辅导Java程序语言、讲解Java，R编程
讲解SPSS|解析Haskell程序
Distributed Computing and Problem
Solving: 7 5hp
Assignment 1
3th November 2020
Innehåll
Part 1 Rules ............................................................................................................................................. 3
Timelimit............................................................................................................................................. 3
Aid....................................................................................................................................................... 3
Submitting ........................................................................................................................................... 3
Presentation ......................................................................................................................................... 3
Grades.................................................................................................................................................. 4
For the grade 3p:.............................................................................................................................. 4
For grade 4p: ................................................................................................................................... 4
For grade 5p: ................................................................................................................................... 4
For the grade U:............................................................................................................................... 4
How do I refer to a source? ................................................................................................................. 5
Part 2 Hands on ....................................................................................................................................... 6
Aim...................................................................................................................................................... 6
The Assignment, the coding!............................................................................................................... 6
Data ................................................................................................................................................. 6
For grade 3 .......................................................................................................................................... 6
For grade 4p: ....................................................................................................................................... 8
For grade 5p: ....................................................................................................................................... 9
References ............................................................................................................................................. 9
Part 1 Rules
Timelimit
Se information in learn.
Aid
This assignment can be solved individually or in pairs but I recommend in pairs. Watch out for
plagiarism.
Plagiarism is the shortness to hand in on someone else's work as their own. Obviously, if it is a
couple's work, then you will have the same solution, but both names need to be on the solution. In
many cases, plagiarism, this can happen unconsciously, and that is why you have to read the
instructions.
Submitting
When submitting apply all options:
Choose to whether write in English or Swedish (don’t mix).
Name your zip file with your username and the grade your aiming for. For example: h16kriha_4.zip in
learn. The submission time will be automatically registered when you submit. Late submissions can’t
grade a higher grade then G(3p) so be careful with the deadlines!
When in a group all need to do individually submission because there is a oral presentation that is
individual even when working in group.
The submission will include one zipfile containing: A report (with answers, sources and a use case
UML), a coding project and a video/videolink with the oral presentation.
Presentation
Everyone in the group needs to:
Add their name to all the documents (in code add all the names as comments, there should not be any
questions regarding who wrote the code). THIS IS VERY IMPOERTANT. Hand in the submission
into the folder in learn before deadline has passed. Late submissions will not be graded higher then G
(3p) and will be examined when the teacher has time for it, it is not guaranteed that it will be graded in
the same time as the ones that handed in “in time”.
The code need to be runnable, make sure to test and check that all you needed to have included is
included in the zip file.
Also everyone in the group need to individually do a presentation that should not succeed 15
minutes (MAX 15 minutes!). You can choose a recording software but its not allowed to have
background music in the recording, your voice needs to be clear. Hand in the link to your video in
your submission. The oral presentation should include:
• Explanation of the code and keywords for each grade, marked with a * in the part 2 Hands on
• Explanation of the solutions and if you hade any problems (how did you overcome them).
• Do a real time run of the code and explain the results that is showing.
Grades
This hand in have four grades U (failed) 3p, 4p and 5p. All the tasks need to be complete and finished
to get a point/grade, there is no subpoints, its Boolean.
For the grade 3p:
All tasks for grade 3p need to be solved, completely solved. Its Boolean, either it works or it does not.
• Create a report where you (can be done in a group):
o Describe the data that you choose to use.
o Discuss the problems and solutions that has come up. (was it hard or easy, did you
find other ways to solve it?)
o Explain the program, what does it do and use at least one source to your explanation,
example a peer-reviewed article or a book.
o Your answers and your source need to be relevant to the task. (see more detailed
information of what is needed in the report and code in part 2 Hands on)
o All your answers and comments must make sense, the teacher should not need to
reread to understand what you wrote.
o Create a use-case UML diagram, se example in figure 2, and include it in the report.
• Solve the coding task, se more information in part 2 Hands on (can be done in a group).
• Do a individual oral presentation (a video).
For grade 4p:
All the tasks in grade 3p need to be completed AND all for grade 4. Its Boolean, either it works, or it
does not. Also, the hand in is submitted in time in learn, se deadlines and time limits in learn.
• Everything for the grade 3 and…
• Do the extra tasks in the coding (se Part 2 Hands on for more information)
• In the report write about the “new” agent from the coding task for grade 4p in Part 2 Hands
on. And also explain Recall and F1 score.
• You need to refer to at least two different sources and at least one needs to be peer-reviewed.
For grade 5p:
All the tasks in grade 3p and 4p need to be completed AND all for grade 5. Its Boolean, either it
works, or it does not. Also, the hand in is submitted in time in learn, see deadlines and time limits in
learn.
• Everything for the grade 3p and 4p and…
• In the report add a section where you write about the algorithm: Naive Bayes for classification.
• Do the extra tasks in the coding (se Part 2 Hands on for more information)
• You need to refer to at least three different sources and at least two needs to be peerreviewed.
For the grade U:
If any of the demands for grade 3p is not fulfilled.
How do I refer to a source?
Literature references that supports your text can be taken from:
Chapter one and two in the course literature Russel and Norvis Atrificial Intelligence: A modern
Approach (3,ed), 2010
Peer-review articles from ACM Digital Library, log on with your school username and password.
Peer-review articles from ScienceDirect (Elsivier Journals), log on with your school username and
password.
Use APA-reference style. It can look like this:
… the Otsu thresholding method (Otsu, 1979) was used ….
And in the reference list it can look like this:
Otsu, N. (1979). A threshold selection method from gray-level histograms.
Automatica, 11(285.296), 23-27
OBS! All articles you quoted must be fully downloaded in this assignment, saved and enclosed in
your submission. (This to simplify and fast the correction procedure)
Part 2 Hands on
Aim
You have come far into your education and has experiences in how to study and how to do
problemsolving. This task can be a challenge but its also a good training for how far you have come.
Some parts come from courses earlier in the program, some parts from this course and some part could
be new. The assignment is fairly open so hence your creativity will be in focus, there is not only one
way to solve this.
The aim is:
Gain insight in how agents communicate with each other (including transferring data) based on a
asynchronous massage passing paradigm. Hence, you should implement the communication part by
making use of the FIPA Agent Communication Language (ACL) Specifications. An ACL Message
contains a number of fields including these four:
• The sender
• The receiver
• The communication Act
• The message content
Grimshaw, 2010.
You should after this know how agents can send data between each other and the act of transmitting
data.
The Assignment, the coding!
Data
Use one or both of these datasets for your machine learning.
• winequality-white.csv - https://archive.ics.uci.edu/ml/machine-learning-databases/winequality/winequality-white.csv
• Students knowledge about direct current systems -
https://archive.ics.uci.edu/ml/datasets/User+Knowledge+Modeling
Often, you must clean and setup the data according to the predetermined rules, which will
suit the computer system. E.g since Excel files carry a lot of meta data, you might want to
transform all files to *.csv, you might want to determine which decimal separator you want
to use, i.e ',', or '.' etc etc.
For grade 4p and 5p in the target column in each file, you must add the string "target". This string
should later be recognized by an agent, who determines if this dataset should be conducted by using
supervised or unsupervised learning.
For grade 3
Create a multi-agent system MAS (Using JADE) where in at least two agents are active.
See description of the suggested architecture in figure 1, where n>2. Since there is more
than one agent, communication must take place in between them. For this reason, one class
out of several useful classes for this is the jade.lang.acl.ACLMessage.
1. Create a USE-CASE Uml diagram to show how you are going to set up your
MAS, which agent should be doing what and is responsible for what. Work
iteratively with this one and update it as something maybe changes in your
approach. This paper might give you an indication on how to do a use-case uml
diagram. Bauer and Odell , UML 2.0 and Agents: How to Build Agent-based
Systems, 2005, but do not over-do the modeling part. One example is shown in
figure 2.
2. The data agent in figure 2 should sense its environment and cache streaming data.
Note in this case there is no sensor, the agent should instead be able to read text
files of type *.csv, *.txt. It should act as a simple reflex agent and should be able
to distribute data/information to other agents. In your documentation you must
describe the content of the data. To keep the complexity level in a more
reasonable fashion the data will not be streamed. Use the datafiles from the data
part above in this instruction report.
3. The classification agent should possess knowledge of supervised learning and
more specifically classification by usage of k-NN. Depending on the incoming data
from the other agent and additional information it must be able to be normalized
or standardized before the classification of test and training takes part. The
classification agent need connection to R via Rserve. So the agent get
data/information from the data agent, connects to R and do the performance
measures.
The ones needed for grade 3p is:
• Preform data validation, use K-fold cross validation* and use the results to compute:
o Confusion matrix*
o Accuracy*
o Precision (exactness of a mode)*
(* means explain these in the oral presentation, what they do and how you interpret their results)
And then present/displays the results back in the Java ouput (in netbeans or
eclipse).
To get started you can go back and check the bookseller example, perhaps there is
key concepts there you can reuse for this assignment. Check out where the buyer
agent compares and selects the cheapest book. This might be a place to insert
something more intelligent like classifying data, i.e. contact R via RServe.
Figure 1 Description of the suggested system
Figure 2 Example of agent skills and dependencies
For grade 4p:
All of grade 3p tasks need to be working.
1. One of your agents has already been developed for performing supervised learning by using
the kNN-algorithm i.e. the Classification Agent. Now, develop another new agent who should
possess the ability to perform unsupervised learning /clustering, by making use of k-Means
clustering. The clustering agents' knowledge and abilities are realized by connecting the agent
to a R via Rserve. The data agent should (as before) forward its' processed data, but since
there are now two agents it depends on the content and structure of the data. This new
clustering agent should only be invoked if and only if there is not a label (i.e a target class like
in supervised learning) containing the string "target" as its column name. The agent should
receive data/info. from the data agent. (See the use case UML below)
2. One of the receiving/analyzing agents should be able to produce and display graphical plots.
The agents' ability is realized by connecting the agent to a R via Rserve and use the script in
and as mentioned above the data is provided from the data agent.
3. Do more performance measures then for grade 3 in addition to those also explain and
use/compute the following concepts on your results (they need to be included in the code, the
oral presentation and the report): Recall (completeness) of a mode* & the F1 Score*.
Environment Data
Agent
Data Acquiring
Extract,
Transform, and
Load data
Classification
Agent
Transmits
data
Rserve
Presents analysis
Environment Data
Agent Extract,
Transform
, and
Load data
Transmits
data Classification
Agent
OR
Data Acquiring
Rserve
Clustering
Agent
Presents results of analysis
Rserve
For grade 5p:
All of grade 3p and 4p tasks need to be working.
1. There are a lot of algorithms for supervised classification and regression learning. Using the
same data set as in grade 3p demonstrate the algorithm Naive Bayes for classification (in the
code). Since this is (probably) a new algorithm for you, start with some examples in the
section References (you find literature there). ln your presentation: Display and present the
code and its execution when you run the code and also explain the classification* oral and in
the report.
References
JADE Tutorial and Primer
Rserve Java APl documentation
Naive Bayes Algorithm
Naive Bayes in R example lris Data
Naive Bayes classification in R using the Titanic data set
Random Forest Algorithm
Random Forest - Fun and Easy Machine Learning (8min)
Random Forests in R I Random Forest Classifier (41min)
Random Forest Tutorial I Random Forest in R (1h 7min)
Good luck
Kristin (Titti) Hane khe@du.se