代写接单- Assignment 1 - FIT5222 Planning and automated reasoning

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Assignment 1 - FIT5222 Planning and automated reasoning

Assignment 1: Flatland Challenge

In this assignment your job is to schedule a set of trains through a railway network.

You need to coordinate every train from its starting station to its destination as quickly as possible. As there can be many trains moving at the same time you need to guarantee that each path is collision-free.

The assignment has three sections, in increasing order of difficulty. The amount of points relative to each question is stated in the question heading. A passing grade is 50%.

Be sure to watch the introductory video on Moodle and to read the Introduction to Flatland documentation which we have prepared for you. Both are available from Moodle.

You must update your flatland code and installation before starting the assignment:

● Under flatland folder

● git pull

● python3 setup.py install

● Now, run command python3 -m pip list , you should see flatland-rl version is

updated to 2.2.4

● (Hint, use python instead of python3 if python points to the right one on your

machine)

Instructions to get code base (in assignment1_2023 branch of piglet repo) for assignment is in the Introduction to Flatland documentation.

When the contest server is ready, you will see your f score upon submission.

QUESTION 1: Warm up (15 points)

You are given start and target locations, one at a time. Your job is to route each train independently from all the rest. In this question collisions are not possible and there is no time dimension.

For this question, you need to implement a successor function for the Flatland domain. You also need to choose an algorithm to help you find paths. You are free to use any of the techniques we have discussed in the lectures, that you have read about in the literature or can write your own new approach.

Your solution will be evaluated on 40 evaluation instances (only staff have these instances) with 2 hours timelimit and each instance has 1 agent. We will compare your sum of individual cost(SIC, for agents did not arrive goal location, its cost will be

Assignment 1 - FIT5222 Planning and automated reasoning

�� = 8 * (��h + h��h��) of the map) and success rate to an optimal solution implemented by teaching team and calculate your score using following method:

�� = ( ��_��_�� + �� * ��_��)/��_�� = ��/��

where ��is the p score of staff implementation. Generally, a good solution has small �� score and large �� score.

Your final score will be �� × 15(since there are 15 points available for this question).

QUESTION 2: Easy mode (25 points)

You are given start and target locations, one at a time, as well as a set of existing paths for trains that are already moving. Your job is to route each train individually while avoiding collisions with all the rest. You are free to use any of the techniques we have discussed in the lectures, that you have read about in the literature or can write your own new approach.

For this question, you need to modify your successor function to account for time. In addition, there might be the situation that the search algorithm failed to find a feasible solution as dynamic obstacles block all possible paths. Just return an empty list in this case.

Furthermore, each action and each location for every computed plan need to be collision-free.

Your solution will be still evaluated on 56 instances with a 2 hours timelimit and your score in this question will again be computed as the sum of individual path costs (SIC) and compared to the best solution from students (and staff)!

Your �� will be computed in the same way as for Question 1. But there are some differences:

● Here we compute �� for each instance.

● Each instance contains multiple agents.

��

● Your final points will be∑ �� ÷ 56 × 25, where �� is instance id.

��

There are up to 25 points available for this question.

Assignment 1 - FIT5222 Planning and automated reasoning

QUESTION 3: Challenge (60 points)

You are given sets of start and target locations at the same time. Your job is to route all the trains simultaneously in a way that is collision-free. But, each agent has an expected arrival time, late arrival will result in a penalty.

You are free to use any of the techniques we have discussed in the lectures, that you have read about in the literature or can write your own new approach.

Now, as all agents are under your control, you need to make all agents reach their goal locations.

In this question agents may run into malfunctions during execution. The evaluator will call the replan function when a new malfunction occurs. Implement the replan function to properly handle malfunction. Refer to the “Introduction to Flatland” document for details about malfunction and replan function.

Your solution will be still evaluated on 56 instances with different difficulty levels in 2 hours and your score in this question will again be computed as the sum of individual path costs (SIC) and compared to the best solution from students (and staff)!

Your �� computation is similar to Question 1. But there are some differences:

● �� = ( ��_��_�� + �� + �� * ��_��)/��_��

● The �� is 2 * ��_��_��.

● Each instance contains multiple agents.

● Each instance’s �� will refer to a baseline implementation �� and an advanced

implementation �� (or best student solution which ever is better):

��

● ∑��

��

÷ 56 × 60, where �� is instance id.

��−��

= ��(0.5 * �� , 0.5) + ��(0.5 * ��−�� ,0)

There are up to 60 points available for this question.

Report (50 points)

You need to create a report that describes your approach to each of the questions. This includes a textual description of your approaches, why you adopted that particular approach and a thorough discussion along with any supplementary material required (such as pseudo code, images, graphs, tables...).

Assignment 1 - FIT5222 Planning and automated reasoning

Report Marking Rubric

Criteria

N 0%-49%

P 50%-59%

C 60%-69%

D 70%-79%

HD 80%-100%

Description of your approach (35 points)

Incomplete or insufficient description of the approach and/or pseudo-code

High-level description of the approach and pseudo-code

+ Discussion and algorithmic analysis. E.g., time, space, completeness, optimality.

+ Reflections: advantages and disadvantages of your approach(es)

+ Numerical experiments, analysing the efficiency of your implementations (e.g. on standard benchmarks and vs. appropriate reference algorithms)

Communication skills

(15 points)

Hard to follow with no clear narrative.

Inadequate or no separation of discussion text into coherent sections.

Writing is not accurate or articulate.

Inadequate supporting materials.

Inadequate or missing referencing.

The writing has a tenuously logical narrative. Some attempt at the expected structural elements (e.g. Intro, conclusion).

Writing is not accurate or articulate most of the time.

The document has few supporting materials (tables, images, pseudo-code) .

The student has attempted to undertake

citing and referencing

with frequent errors.

The text has a clear logical narrativae and expected structural elements (e.g. intro, conclusion).

Writing is not accurate or articulate most of the time.

There are some supporting materials (tables, images, pseudo-code) but not well integrated with the rest of the text.

The student follows the requirements for citing and referencing, with some notable errors.

The writing is well composed and has a clear and logical narrative and is well structured.

Writing is generally accurate and articulate.

The document has appropriate supporting materials that are well integrated with the rest of the text.

The student follows the requirements for citing

and referencing, with

some minor errors.

The writing is very well composed and has a very clear and logically formed narrative as a whole.

Writing is accurate and articulate.

The document is expertly structured in the style of a scientific report, including appropriate supporting materials that clearly improve the quality of associated discussion.

The student follows the requirements for citing and referencing.

Assignment 1 - FIT5222 Planning and automated reasoning

Bonus Points

We will issue bonus points for students implementing multiple approaches for the same problem, and/or for implementations of algorithms from the scientific literature that are not discussed during tutorials/lectures (e.g., from one of the recommended papers or elsewhere). The size of the bonus depends on how ambitious the implementation is, its effectiveness and the quality of the writeup.

BONUS POINTS CAN MAKE THE DIFFERENCE BETWEEN ‘D’ and ‘HD’

Grades

The total points for the assignment is 150. A passing grade is 50% of total points, which is 75 points.

SUBMISSION

The assignment is due on 17th April 2022 23:55 pm (Monday of Week 7) Submit to Contest Server:

● The contest server and submission instruction will be released soon. You will receive a notification when it’s ready.

● Follow the FIT5222 Flatland Challenge Submission Instruction to submit your codes to contest server.

● Your code will be auto marked on the contest server, thus you must submit it to the contest server.

Submit to Moodle:

1. Your implementation source codes, in a single directory called "src" (you can copy everything in the piglet folder to "src"). Zip the codes directory with file name last_name_student_id_flatland.zip. (For example, Chen_123456_flatland.zip)

2. The report describing your approaches as a single pdf file. Name the pdf as last_name_student_id_report.pdf. (For example, Chen_123456_report.pdf)

3. Submit the two files to the Moodle assignment submission page. (Do not zip the pdf report, as moodle needs the pdf to generate turnitin report).