7COM1034: Python Programming - Theory and Practice of Articial Intelligence - Search and Bayesian Update - Essay Writing Assessment Answer

Code: 7COM1034

Theory and Practice of Articial Intelligence Assessment Answer

Assignment Task: 7COM1034 This part of the coursework consists of three components, one for Search, one for Bayesian Update, and a mini-essay (discussion). Each of first two contains various tasks, and the discussion task is to give a high-level picture of how these problems t together. The core tasks should be carried out Frist. The advanced tasks are considerably more dicult and it is strongly advised not to attempt them before all core tasks have been completed. 1.1 Description The task consists of programming a Python implementation of a solver for the Decanting Task. The Task - 7COM1034 Based on the search algorithms covered in the lecture, write a Python program that starts from some starting state, (f1; f2; f3) and moves according to the rules until it reaches a given goal state for the decanting task. Your solution must at least be able to solve the example from Sec. 1.1.1 but should be more general than that, in that it allows for a larger number of vessels and different fillings (see below for a variant). For this, you have to adapt the search algorithms introduced in the lecture presented in the lecture and apply it to a Decant class which you have to write. Keep in mind that a naive depth-the first search need not work, as the problem can repeat positions. 1.1.4 Detailed Instructions and Marking Scheme - 7COM1034 Core Tasks You need to write a class Decant and dene for it (at least) the following class methods: 1. start(self): returns the starting state for the decanting task. Hint: There are dierent ways of representing the board | whatever you choose to do, make sure you give a clear comment how you decided to represent the state. 2. goal(self, node): returns True if the conguration node is a goal conguration, i.e. if it fulls the target requirement (in the example from Sec. 1.1.1, two vessels with 4 litres each). 3. succ(self, node): yields successively all the successors of the conguration indicated by the node. Furthermore, you will have to write - 7COM1034 4. the code importing the various modules 5. the code running the search and printing the results Advanced Tasks Once you have successfully implemented the depth-rst or breadth-rst solution for the Decanting Task, you can proceed to implement a variant of the problem for additional marks. 6. demonstrate the operation of your solution by solving a variant of the rst task, with capacities (c1; c2; c3) = (7; 4; 3), initial state (f1; f2; f3) = (7; 0; 0) (all 7 litres in the first vessel at the beginning), target state (2; 2; 3). 7. modify your class to handle the following variations of the problem: You have two vessels, one with 4 and one with 9 litres volume. You also have a tap (which allows you to completely ll a vessel) and a sink (which allows you to completely empty a vessel). How can you use the vessels to obtain exactly 6 litres of liquid (collected in a single vessel)? 2 Task: Bayesian Update | A Whale Watching" Scenario - 7COM1034 2.1 Description - 7COM1034 The task consists of writing a Python program which simulates a ship trying to reach a whale in a 10  10 grid world. More precisely, the ship moves through the grid world and measures (e.g. by sonar") a distance to the whale. From it, it deduces where the whale could be (using a Bayesian model), moves, measures again, etc. until it knows where the whale is. More precisely, the skeleton of the Python program is provided with the le whale_fillin.py (Fig. 1) and the task consists of filling in the missing components. 2.1.2 The Task - 7COM1034 The task of this assignment is to ll in the missing parts of the program, indicated by three dots ..." in the Python program whale_fillin.py (Fig. 1). Unless stated, the tasks are core tasks. 3 Task: Discussion - 7COM1034 3.1 Description In Assignment 1, you needed to consider a search problem and in Assignment 2 the update of a model of the uncertain state of a system. In the minesweeper problem from the lecture, you nd a combination of these ideas: you need to estimate the state of the system and you need to solve it (here: nd the mine) as quickly as possible. In the minesweeper example, the problem is also that you trade o safety for speed | a more aggressive search will increase the likelihood of stepping on the mine, but accelerate identication of its location as compared to a more conservative one. Sketch and discuss an algorithm (verbal pseudocode is sucient, no need for a full program) to nd the whale as quickly as possible when your ship can only make single steps and discuss whether and, if yes, how the algorithm would need to be modied to operate on the mine problem. Discuss, in particular, how this idea is related to the puzzle task from Sec. 1 and the whale search task from Sec. 2. You should write 1,000 words (less if you have instructive illustrations/diagrams). You will get marks for: 7COM1034 1. Research on above issues (e.g. brief literature review on the link between search algorithms and state identication, including, but not limited to partially observable systems). Do not forget to cite your sources! Avoid plagiarism! [3 marks] 2. Sketching an algorithm that would address the double problem of searching and identifying the state (no need for a detailed Python code). [4 marks] 3. Discussing the algorithm in light of the minesweeper problem and the whale watching problem.

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