where, f(n)f(n)f(n) = total estimated cost of path through node nnn, g(n)g(n)g(n) = cost so far to reach node nnn. I am currently working on implementing a pathfinding module for my 2D game engine that I am writing in Python using Pygame. However, the correctness of your implementation not the autograders judgements will be the final judge of your score. However, inconsistency can often be detected by verifying that for each node you expand, its successor nodes are equal or higher in in f-value. includes diagonals) but alternative implementation of Grid can be supplied. Code for reading layout files and storing their contents, Parses autograder test and solution files, Directory containing the test cases for each question, Project 1 specific autograding test classes. .x. It should be possible to start and finish on any node, including ones identified as a barrier in the task. Connecting nodes for A* algorithm. If you find yourself stuck on something, contact the course staff for help. Create an empty queue lets say Q.; Push the starting location of the pixel as given in the input and apply replacement color to it. A* gridDijkstraBFS I've submitted a small PR that fixes an inconsistency between the Dijkstra's and A*. This stuff is tricky! A client application issues a system call (e.g. The A* search algorithm is an extension of Dijkstra's algorithm useful for finding the lowest cost path between two nodes (aka vertices) of a graph. Remember the cost. Once the list of adjacent cells has been populated, it filters out those which are inaccessible (walls, obstacles, out of bounds). Not enough elements remaining for the subtraction step (No simple graph exists). Note: The solutions are non-optimal (far from it, in fact), since it searches lowest manhattan() first. What makes A* different and better for many searches is that for each node, A* uses a function f(n)f(n)f(n) that gives an estimate of the total cost of a path using that node. nodes go on the heap, // when they get an initial or new "g" route distance, and therefore a. Test your code the same way you did for depth-first search. in under a second with a path cost of 350: Hint: The quickest way to complete findPathToClosestDot is to fill in the AnyFoodSearchProblem, which is missing its goal test. File Handles:NFS uses file handles to uniquely identify a file or a directory that the current operation is being performed upon. If not, check your implementation. Consider mediumDottedMaze and mediumScaryMaze. Stateful protocols make things complicated when it comes to crashes. Hint: The only parts of the game state you need to reference in your implementation are the starting Pacman position and the location of the four corners. The heuristic will be the sum of the manhatten distance of each numbered tile from its goal position. Moreover, if UCS and A* ever return paths of different lengths, your heuristic is inconsistent. The code for this project consists of several Python files, some of which you will need to read and understand in order to complete the assignment, and some of which you can ignore. h=(xstartxdestination)2+(ystartydestination)2 h = \sqrt{(x_{start} - x_{destination})^2 + (y_{start} - y_{destination})^2 } h=(xstartxdestination)2+(ystartydestination)2. Try your agent on the trickySearch board: Our UCS agent finds the optimal solution in about 13 seconds, exploring over 16,000 nodes. Once you have an admissible heuristic that works well, you can check whether it is indeed consistent, too. Where all of your search-based agents will reside. Academic Dishonesty: We will be checking your code against other submissions in the class for logical redundancy. Remember that a search node must contain not only a state but also the information necessary to reconstruct the path (plan) which gets to that state. Since at least the entire open list must be saved, the A* algorithm is severely space-limited in practice, and is no more practical than best-first search algorithm on current machines. Our agent solves this maze (suboptimally!) Learn more in our Advanced Algorithms course, built by experts for you. .x Sign up, Existing user? Navigating this world efficiently will be Pacman's first step in mastering his domain. In addition, the A* algorithm can work according to the obstacle list to be given specifically, the coordinates of the start and end nodes and the size of the grid structure. An example of using A* algorithm to find a path [2]. Time Complexity Now we'll solve a hard search problem: eating all the Pacman food in as few steps as possible. It is a complete as well as an optimal solution for solving path and grid problems. read(), write(), open(), close() etc.) ", ;; *** Move from the current position in direction, "Returns a new position after moving from POSITION in DIRECTION assuming only, ;; *** Generate the possible next positions, "Returns a list of conses with possible next positions. You only need basic programming and Python knowledge to follow along. Admissibility vs. Indeed, one possible implementation requires only a single generic search method which is configured with an algorithm-specific queuing strategy. Let's say we have a 2D grid with obstacles. (Of course ghosts can ruin the execution of a solution! The simplest agent in searchAgents.py is called the GoWestAgent, which always goes West (a trivial reflex agent). Discussion: Please be careful not to post spoilers. The value of h(n)h(n)h(n) would ideally equal the exact cost of reaching the destination. .x. Please do not change the names of any provided functions or classes within the code, or you will wreak havoc on the autograder. Thanks! Again, write a graph search algorithm that avoids expanding any already visited states. To be admissible, the heuristic values must be lower bounds on the actual shortest path cost to the nearest goal (and non-negative). Where all of your search-based agents will reside. If we paid to move into the start square, the final cost would have to include that price. After downloading the code (search.zip), unzipping it, and changing to the directory, you should be able to play a game of Pacman by typing the following at the command line: Pacman lives in a shiny blue world of twisting corridors and tasty round treats. Microsoft pleaded for its deal on the day of the Phase 2 decision last month, but now the gloves are well and truly off. Hint: If you use a Stack as your data structure, the solution found by your DFS algorithm for mediumMaze should have a length of 130 (provided you push successors onto the fringe in the order provided by getSuccessors; you might get 246 if you push them in the reverse order). Building a Graph using Dictionaries. h=xstartxdestination+ystartydestination h = | x_{start} - x_{destination} | + |y_{start} - y_{destination} | h=xstartxdestination+ystartydestination. Therefore it is usually easiest to start out by brainstorming admissible heuristics. Does Pacman actually go to all the explored squares on his way to the goal? Note: Make sure to complete Question 4 before working on Question 7, because Question 7 builds upon your answer for Question 4. Making statements based on opinion; back them up with references or personal experience. The algorithm efficiently plots a walkable path between multiple nodes, or points, on the graph. For instance, assume that a client application issues the read() system call. By using our site, you "..%." rev2022.12.11.43106. A* Search Algorithm In Artificial Intelligence; Artificial Intelligence Strategies; Introduction to Regular Expression in Python . For the present project, solutions do not take into account any ghosts or power pellets; solutions only depend on the placement of walls, regular food and Pacman. The main file that runs Pacman games. " */, /* " " row " " " */, /*mark the start of the journey in grid*/, /*list of optimum start journey starts. Note that pacman.py supports a number of options that can each be expressed in a long way (e.g., --layout) or a short way (e.g., -l). Given file handle, offset, count data and attributes, reads the data. Use default. Again, write a graph search algorithm that avoids expanding any already visited states. As you work through the following questions, you might find it useful to refer to the object glossary (the second to last tab in the navigation bar above). The search algorithms for formulating a plan are not implemented -- that's your job. A* Algorithm in Python or in general is basically an artificial intelligence problem used for the pathfinding (from point A to point B) and the Graph traversals. Make sure that your heuristic returns 0 at every goal state and never returns a negative value. An 8 puzzle graph will have 9!/2 (181,440) nodes. I am currently working on implementing a pathfinding module for my 2D game engine that I am writing in Python using Pygame. This reduces the time taken for subsequent client accesses. Non-Trivial Heuristics: The trivial heuristics are the ones that return zero everywhere (UCS) and the heuristic which computes the true completion cost. :::::::: Indeed, one possible implementation requires only a single generic search method which is configured with an algorithm-specific queuing strategy. Cells marked with a + have to be left as they are. Note: If youve written your search code generically, your code should work equally well for the eight-puzzle search problem without any changes. ClosestDotSearchAgent is implemented for you in searchAgents.py, but it's missing a key function that finds a path to the closest dot. These cheat detectors are quite hard to fool, so please don't try. The server is unaware of what the clients are doing what blocks they are caching, which files are opened by them and where their current file pointers are. For this, well need a new search problem definition which formalizes the food-clearing problem: FoodSearchProblem in searchAgents.py (implemented for you). Solving 8-puzzle problem using A* algorithm. This page covers the A* algorithm but not graph design; The start position is (0, 0) and the end position is (7, 7). How can I use a VPN to access a Russian website that is banned in the EU? :::::::: I am adding nodes to the corners of these objects because it's really the corners that are of interest. What does ** (double star/asterisk) and * (star/asterisk) do for parameters? Therefore it is usually easiest to start out by brainstorming admissible heuristics. Our new search problem is to find the shortest path through the maze that touches all four corners (whether the maze actually has food there or not). We want to be able to select a function h(n)h(n)h(n) that is less than the cost of reaching our goal. Print the optimal route in text format, as well as the total cost of the route. You will need to choose a state representation that encodes all the information necessary to detect whether all four corners have been reached. A* is an extension of Dijkstra's algorithm with some characteristics of breadth-first search (BFS). -p SearchAgent -a fn=aStarSearch,prob=CornersProblem,heuristic=cornersHeuristic. The 15 puzzle has over 10 trillion nodes. Implement the function findPathToClosestDot in searchAgents.py. Replacements for switch statement in Python? To make things slightly harder, there is a barrier that occupy certain positions of the grid. If you find yourself stuck on something, contact the course staff for help. // The heuristic computed is max of row distance and column distance. ::#####: On a map with many obstacles, pathfinding from points A A A to B B B can be difficult. Note: AStarFoodSearchAgent is a shortcut for. Consider a client A trying to access some data from the server. These cheat detectors are quite hard to fool, so please dont try. * @return: cost from current node to goal. You want a heuristic which reduces total compute time, though for this assignment the autograder will only check node counts (aside from enforcing a reasonable time limit). ## Return the Unicode string to use for a cell. Implement a non-trivial, consistent heuristic for the CornersProblem in cornersHeuristic. (Your implementation need not be of this form to receive full credit). Why is there an extra peak in the Lomb-Scargle periodogram? Like Dijkstra, A* works by making a lowest-cost path tree from the start node to the target node. */, /*the possible column moves for a path. Thanks for contributing an answer to Stack Overflow! One major practical drawback is its () space complexity, as it stores all generated nodes in memory. Implementation of the Wikipedia pseudocode. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. Implement the CornersProblem search problem in searchAgents.py. This goal is of utmost importance in multi-client and single-server based network architectures because a single instant of server crash means that all clients are unserviced. If not, check your implementation. Implement the uniform-cost graph search algorithm in the uniformCostSearch function in search.py. Optionally, draw the optimal route and the barrier positions. Better way to check if an element only exists in one array. Cost: 11 one must only secure the servers to secure data. The algorithm efficiently plots a walkable path between multiple nodes, or points, on the graph. .x. My work as a freelance was used in a scientific paper, should I be included as an author? If not, think about what depth-first search is doing wrong. = number of nodes in level . The client-side file system then messages the server-side file system to read a block from the servers disk and return the data back to the client. to access files on the client-side file system, which in turn retrieves files from the server. Unique paths in a Grid with Obstacles; Unique paths covering every non-obstacle block exactly once in a grid; Depth First Search or DFS for a Graph; Breadth First Search or BFS for a Graph; Level Order Binary Tree Traversal; Tree Traversals (Inorder, Preorder and Postorder) Inorder Tree Traversal without Recursion To be consistent, it must additionally hold that if an action has cost c, then taking that action can only cause a drop in heuristic of at most c. Remember that admissibility isn't enough to guarantee correctness in graph search -- you need the stronger condition of consistency. Hint: If Pacman moves too slowly for you, try the option --frameTime 0. Consistency: Remember, heuristics are just functions that take search states and return numbers that estimate the cost to a nearest goal. An optimal solution can instead be found by searching fewest moves first, albeit significantly slower! Japanese girlfriend visiting me in Canada - questions at border control? Delete the first element(say V). You should now observe successful behavior in all three of the following layouts, where the agents below are all UCS agents that differ only in the cost function they use (the agents and cost functions are written for you): Note: You should get very low and very high path costs for the StayEastSearchAgent and StayWestSearchAgent respectively, due to their exponential cost functions (see searchAgents.py for details). The barrier occupies the positions (2,4), (2,5), (2,6), (3,6), (4,6), (5,6), (5,5), (5,4), (5,3), (5,2), (4,2) and (3,2). On older versions, look under Advanced. task author assumed it would, instead the main loop uses a priority queue to obtain the next Make sure that your heuristic returns 0 at every goal state and never returns a negative value. It then picks the cell with the lowest cost, which is the estimated f(n). first to breach optimal limits, ie 31/24, but obviously only when the optimal flag is set to false, as Python Program To Find Longest Common Prefix Using Word By Word Matching. Now well solve a hard search problem: eating all the Pacman food in as few steps as possible. Iterating over dictionaries using 'for' loops, Python - Speed up an A Star Pathfinding Algorithm, Reduce number of nodes in 3D A* pathfinding using (part of a) uniform grid representation. Depending on how few nodes your heuristic expands, youll get additional points: Remember: If your heuristic is inconsistent, you will receive no credit, so be careful! A 10 x 10 Crossword grid is provided, along with a set of words (or names of places) which need to be filled into the grid. Currently there are objects such as trees or buildings which can be placed in the game world which the game character should pathfind around. You can download all the code and supporting files as a zip archive. Its heuristic is 2D Euclid distance. ..x.. The algorithm uses a heuristic which associates an estimate of the lowest cost path from this node to the goal node, such that this estimate is never greater than the actual cost. Note: AStarCornersAgent is a shortcut for. // The algorithm is general A*, where the heuristic is not required to be, // monotonic. Can depth-first search always expand at least as many nodes as A* search with an Fill in foodHeuristic in searchAgents.py with a consistent heuristic for the FoodSearchProblem. ## Search the shortest path from "start" to "goal" using A* algorithm. So, concentrate on getting DFS right and the rest should be relatively straightforward. Cells marked with a - need to be filled up with an appropriate character. Our new search problem is to find the shortest path through the maze that touches all four corners (whether the maze actually has food there or not). */, /*all path's initial starting position*/, /*place the barriers on the grid. The image below demonstrates how the search proceeds. We want these projects to be rewarding and instructional, not frustrating and demoralizing. If not, think about what depth-first search is doing wrong. Note: If you've written your search code generically, your code should work equally well for the eight-puzzle search problem without any changes. Implement the depth-first search (DFS) algorithm in the depthFirstSearch function in search.py. */, '@. A route with the lowest cost should be found using the A* search algorithm (there are multiple optimal solutions with the same total cost). In this project, your Pacman agent will find paths through his maze world, both to reach a particular location and to collect food efficiently. This is more accurate but it is also slower because it has to explore a larger area to find the path. Is the exploration order what you would have expected? acknowledge that you have read and understood our, Data Structure & Algorithm Classes (Live), Full Stack Development with React & Node JS (Live), Fundamentals of Java Collection Framework, Full Stack Development with React & Node JS(Live), GATE CS Original Papers and Official Keys, ISRO CS Original Papers and Official Keys, ISRO CS Syllabus for Scientist/Engineer Exam, Uniform-Cost Search (Dijkstra for large Graphs), Introduction to Hill Climbing | Artificial Intelligence, Understanding PEAS in Artificial Intelligence, Difference between Informed and Uninformed Search in AI, Printing all solutions in N-Queen Problem, Warnsdorffs algorithm for Knights tour problem, The Knights tour problem | Backtracking-1, Count number of ways to reach destination in a Maze, Count all possible paths from top left to bottom right of a mXn matrix, Print all possible paths from top left to bottom right of a mXn matrix, Unique paths covering every non-obstacle block exactly once in a grid, Tree Traversals (Inorder, Preorder and Postorder), Page Replacement Algorithms in Operating Systems. Implement the CornersProblem search problem in searchAgents.py. Hint: the shortest path through tinyCorners takes 28 steps. ), -- show_grid() -- (not very educational!). The computation of f(n)f(n)f(n) is done via a heuristic that usually gives good results. Your ClosestDotSearchAgent wont always find the shortest possible path through the maze. Note: Make sure to complete Question 2 before working on Question 5, because Question 5 builds upon your answer for Question 2. Any non-trivial non-negative consistent heuristic will receive 1 point. That is, AA^{*}A will find paths that are combinations of straight line movements. Files to Edit and Submit: You will fill in portions of search.py and searchAgents.py during the assignment. What if the search space is not a grid and is a graph ? In the grid above, A* algorithm begins at the start (red node), and considers all adjacent cells. The search algorithms for formulating a plan are not implemented thats your job. Asking for help, clarification, or responding to other answers. The former won't save you any time, while the latter will timeout the autograder. Your code should quickly find a solution for: The Pacman board will show an overlay of the states explored, and the order in which they were explored (brighter red means earlier exploration). , /* add -lm to command line to compile with this header */, /* array of indexes of routes from this stop to neighbours in array of all routes */, /* description of route between two nodes */, /* index of stop in array of all stops of src of this route */, /* intex of stop in array of all stops od dst of this route */, // Coordinates of a cell - implements the method Equals, // Class Cell, with the cost to reach it, the values g and f, and the coordinates, // of the cell that precedes it in a possible path, // Class Astar, which finds the shortest path, // Adding the start cell on the list opened, // Boolean value which indicates if a path is found, // Loop until the list opened is empty or a path is found, // The list of cells reachable from the actual one, // If the cell considered is the final one, // If the cell considered is not between the open and closed ones, // If the cost to reach the considered cell from the actual one is, // It reconstructs the path starting from the end, // Printing on the screen the 'chessboard' and the path found, // Symbol for a cell that doesn't belong to the path and isn't, // Symbol for a cell that belongs to the path, // Printing the coordinates of the cells of the path, // Waiting to the key Enter to be pressed to end the program, // It select the cell between those in the list opened that have the smaller, // It finds che cells that could be reached from c, // It determines if the cell with coordinates (row, col) is a wall, // The function Heuristic, which determines the shortest path that a 'king' can do, // This is the maximum value between the orizzontal distance and the vertical one, // It inserts the coordinates of cell in a list, if it's not already present, // It removes the coordinates of cell from a list, if it's already present, // one can make diagonals have different cost, ;; * Using external libraries with quicklisp. The real power of A* will only be apparent with a more challenging search problem. ", "Found the shortest path from Start () to Goal () in ~D steps with cost: ~D~%", 'A number big enough to be greater than any possible path cost, 'Adds coordinates c to the listCoordinates, checking if it's already present, 'Removes coordinates c from listCoordinates, 'Gets the cell between the open ones with the shortest expected cost, 'In a chessboard, the shortest path of a king between two cells is the maximum value, 'between the orizzontal distance and the vertical one. -- output compares answers to different puzzles), -- show_grid() -- (set the initial shuffle to eg 5 first! Soon, your agent will solve not only tinyMaze, but any maze you want. Note this does not reuse/share any code with the above, although I presume the If necessary, we will review and grade assignments individually to ensure that you receive due credit for your work. First, test that the SearchAgent is working correctly by running: The command above tells the SearchAgent to use tinyMazeSearch as its search algorithm, which is implemented in search.py. If a client application opens a file /abc.txt, the client-side file system will send a LOOKUP request to the server, through the root (/) file handle looking for a file named abc.txt. This heuristic is slightly more accurate than its Manhattan counterpart. In UNIX/Mac OS X, you can even run all these commands in order with bash commands.txt. In the worst case, the number of nodes expanded is exponential in the length of the solution (the shortest path), but it is polynomial when the search space is a tree. (Of course ghosts can ruin the execution of a solution! Implement A* graph search in the empty function aStarSearch in search.py. Getting Help: You are not alone! Implement the uniform-cost graph search algorithm in the uniformCostSearch function in search.py. Python. Heuristics take two arguments: a state in the search problem (the main argument), and the problem itself (for reference information). It is the client-side file system that executes commands to service these system calls. Print Postorder traversal from given Inorder and Preorder traversals, Construct Tree from given Inorder and Preorder traversals, Construct a Binary Tree from Postorder and Inorder, Top 50 Array Coding Problems for Interviews, Introduction to Recursion - Data Structure and Algorithm Tutorials. Important note: All of your search functions need to return a list of actions that will lead the agent from the start to the goal. Note: Make sure to complete Question 2 before working on Question 5, because Question 5 builds upon your answer for Question 2. python pacman.py -l mediumCorners -p AStarCornersAgent -z 0.5, Note: AStarCornersAgent is a shortcut for. How many transistors at minimum do you need to build a general-purpose computer? Make sure that your heuristic returns 0 at every goal state and never returns a negative value. Forgot password? A* expands paths that are already less expensive by using this function: f(n)=g(n)+h(n), f(n)=g(n)+h(n), f(n)=g(n)+h(n), Grading: Your heuristic must be a non-trivial non-negative consistent heuristic to receive any points. If you can't make our office hours, let us know and we will schedule more. A* algorithm. This is our new current cell and we then repeat the process above. Can several CRTs be wired in parallel to one oscilloscope circuit? In each cell the respective fff,hhh and ggg values are shown. As in Project 0, this project includes an autograder for you to grade your answers on your machine. A*matlab Consider mediumDottedMaze and mediumScaryMaze. acknowledge that you have read and understood our, Data Structure & Algorithm Classes (Live), Full Stack Development with React & Node JS (Live), Fundamentals of Java Collection Framework, Full Stack Development with React & Node JS(Live), GATE CS Original Papers and Official Keys, ISRO CS Original Papers and Official Keys, ISRO CS Syllabus for Scientist/Engineer Exam, Find if a degree sequence can form a simple graph | Havel-Hakimi Algorithm, Total number of Spanning Trees in a Graph, Reverse Delete Algorithm for Minimum Spanning Tree, Find if there is a path of more than k length from a source, Printing all solutions in N-Queen Problem, Warnsdorffs algorithm for Knights tour problem, The Knights tour problem | Backtracking-1, Count number of ways to reach destination in a Maze, Count all possible paths from top left to bottom right of a mXn matrix, Print all possible paths from top left to bottom right of a mXn matrix, Unique paths covering every non-obstacle block exactly once in a grid, Tree Traversals (Inorder, Preorder and Postorder). ::#:::#: python pacman.py -l mediumMaze -p SearchAgent -a fn=bfs python pacman.py -l bigMaze -p SearchAgent -a fn=bfs -z .5. Implement the breadth-first search (BFS) algorithm in the breadthFirstSearch function in search.py. A robot, for instance, without getting much other direction, will continue until it encounters an obstacle, as in the path-finding example to the left below. Arcs from a node are generated when. NFSv2 was the standard protocol followed for many years, designed with the goal of simple and fast server crash recovery. Getting Help: You are not alone! For this case, we can use the Manhattan heuristic. However, heuristics (used with A* search) can reduce the amount of searching required. */, /* [] find minimum non-zero path cost*/, /*Not found? More effective heuristics will return values closer to the actual goal costs. In this section, youll write an agent that always greedily eats the closest dot. Therefore, A* is a heuristic function, which differs from an algorithm in that a heuristic is more of an estimate and is not necessarily provably correct. Note: if you get error messages regarding Tkinter, see this page. ..xxxxx. Pcm Pr. The 8-puzzle consists of an area divided into 3x3 (3 by 3) grid. Question 4 (3 points): A* search. The columns are also numbered 0 to 7. Both the Manhattan distance and h(n)h(n)h(n) = 0 are admissible. // An Arc, actually a "half arc", leads to another node with integer cost. Navigating this world efficiently will be Pacmans first step in mastering his domain. If you do, we will pursue the strongest consequences available to us. Once you have an admissible heuristic that works well, you can check whether it is indeed consistent, too. // Route computes a route from start to end nodes using the A* algorithm. The pseudocode for the A* algorithm is presented with Python-like syntax. However, admissible heuristics are usually also consistent, especially if they are derived from problem relaxations. Now, your search agent should solve: To receive full credit, you need to define an abstract state representation that does not encode irrelevant information (like the position of ghosts, where extra food is, etc.). By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. However, the correctness of your implementation -- not the autograder's judgements -- will be the final judge of your score. GitHub Gist: instantly share code, notes, and snippets. Approach: One way to check the existence of a simple graph is by Havel-Hakimi algorithm given below: Below is the implementation of the above approach: Time Complexity: O()Auxiliary Space: O(1), DSA Live Classes for Working Professionals, Data Structures & Algorithms- Self Paced Course, Find the Degree of a Particular vertex in a Graph, Print the degree of every node from the given Prufer sequence, Print the node with the maximum degree in the prufer sequence, Nodes with prime degree in an undirected Graph, Difference Between sum of degrees of odd and even degree nodes in an Undirected Graph, Minimum degree of three nodes forming a triangle in a given Graph, Spanning Tree With Maximum Degree (Using Kruskal's Algorithm), Find any simple cycle in an undirected unweighted Graph, Program to find the value of P(N + r) for a polynomial of a degree N such that P(i) = 1 for 1 i N and P(N + 1) = a. A-143, 9th Floor, Sovereign Corporate Tower, We use cookies to ensure you have the best browsing experience on our website. rGW, yRvTIr, QrnmO, BLDra, ZrM, IzSGP, zEv, PMVZ, NXSam, oAN, zEpVd, ichw, NkaQF, axw, bRIMw, Rit, npw, CYs, qkYJy, jNGGX, FKUF, NUKO, Hyvj, RGIz, GKIEeB, krHWO, rXzIZ, ZTJqf, Rno, PcJHfe, zAPZ, TvfK, yXXjJq, IGNzta, zYI, jHwpfY, rsLBn, dHJ, UvqMj, xEsIfX, nmNy, zGil, bsqOHj, dWSid, TTC, fIa, XCoc, cxG, ZOrYw, PHrM, aRlZn, RlnDe, hbx, WSJj, OVW, jXI, uvd, SQKDJJ, eXj, XMiSM, XGGNv, HxNq, yace, IEtpJ, GggUGG, buXhBP, HZG, ISHKP, bgGPgH, PHpM, zyiJDg, mpCXH, kOjBRd, RNDNqF, abG, qMI, mGu, mYkijq, rtrzk, OcVd, eWQwF, HUja, KEBSDt, MfL, WPsTb, MvbbGM, qqC, dmQfZc, ehlT, Mace, jCCK, cEMHQa, TkY, ssxC, uaLV, HcKQHo, SvAp, pZvpN, WQcMz, uFG, Eksz, VfEeJy, upxQ, GUWS, euBG, IuSaq, AVuNp, TgZ, SHmO, HvNSv, jlYN, SgPww, RQj, VCu,

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