F29AI : Artificial Intelligence and Intelligent Agents - Search and Automated Planning - Engineering Assignment Help

Assignment Task :

A* Search - Problem description 

The above grids represent two problem environments where an agent is trying to find a path from the start  location (S) to the goal location (S). The agent can move to an adjacent square provided the square is white or  grey. The agent cannot move to a black square which represents a wall. No diagonal movement is allowed. Moving  into a white square has a cost of 1. Moving into a grey square has a cost of 3. 

What to do: Undergraduate students, 1-year Edinburgh postgraduate students, and all  Dubai postgraduate students 

Implement a solution to the grid problem in Java using A* search. Starter code has been provided for you and is  available in the accompanying zip file. In particular, the code in the package uk.ac.hw.macs.search is a set of  classes that can be used to represent a search problem. To implement a specific search problem, you will need to  do the following: 

1. Define a class that implements the State interface.

This should include the following:

a. A method for determining whether a state is a goal state (isGoal()) 

b. A method for computing the heuristic value of a state (getHeuristic()) 

2. Define a class that implements the SearchOrder interface. This interface has one public method,  addToFrontier, that is used to add a set of nodes to the frontier. You can use the costs and/or heuristic  values to determine the order that nodes are added to the frontier 

The classes in the uk.ac.hw.macs.search.example package show examples of these two interfaces being used to  implement depth-first search and breadth-first search, as well as a simple integer-based state. The Main class in  this package shows an example of how to use the classes. 

To solve the problem, you will also need to implement the following: 

1. An appropriate encoding of the state in the grid by implementing the State interface appropriately,  including methods for detecting a goal state and computing a heuristic value. You will need to choose or  design an appropriate heuristic to use for your search. Include a description of the heuristic in the  comments of your code. 

2. A class implementing A* search by implementing the SearchOrder interface and implementing  addToFrontier appropriately 

Test your code on the two grid problems provided by running A* search on them. Submit the code for the  implementation as well as the output. Do not change any of the classes in the uk.ac.hw.macs.search: we will test  your implementation against the provided classes.

What to do: 2-year Edinburgh postgraduate students only 

Describe a solution to the grid problem using A*search. In particular, you should do the following: 1. Draw a graph (with nodes and edges) to represent each of the grid problems as a search problem. Label  each of the nodes in your graph and include appropriate costs on the edges. 

2. Choose or design an appropriate heuristic to use for both graphs. Describe how your heuristic operates  and include the heuristic values on each node in your graph. 

3. Apply A* search to each grid and list the states expanded and the goal path for each grid. You do not need  to provide a full derivation for each search (unless you wish to do so), however, you should provide at  least the first 5 steps of each derivation with calculations for the f values to demonstrate you understand  the application of the A* algorithm in your graph. 

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