GitHub - womackj1/CS6601: Data and Instructions for CS6601 Homework Assignment womackj1 CS6601 Code Issues Pull requests Actions Projects Security Insights main 1 branch 0 tags Code womackj1 Merge pull request #1 from tangemicioglu/main 3cee3ec on Oct 21, 2020 4 commits Failed to load latest commit information. If nothing happens, download GitHub Desktop and try again. This project taught me a few lessons, recounted in our paper: 1) user studies may need to involve training the user as much as the system; after all, computers are flawless at consistent reproduction of actions, but people demonstrate significant variance, and 2) because we dont understand basic human operations such as perception, it is nearly impossible to directly code an approach. In particular, what I felt was missing from the book was an integrative approach that tackles systems design design by incorporating multiple AI techniques. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. git clone https://github.gatech.edu/omscs6601/assignment_2.git Setup Activate the environment: conda activate ai_env In case you used a different environment name, to list of all environments you have on your machine you can run conda env list. The shifted perspective significantly aids comprehension. tridirectional_search() should return a path between all three nodes. Provide the precise relationshipof cause and effect. It is very easy to encounter exponential growth in search spaces, which quickly leads to intractable problems. You will be implementing game playing agents for a variant of the game Isolation. You may also want to look at the Tri-city search challenge question on Canvas. CS6601 Assignment 4 | Kaggle search Something went wrong and this page crashed! Now we are ready for the moment of truth. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. To review, open the file in an editor that reveals hidden Unicode characters. (644 Documents). Then what we want you to do is to start at node a and expand like in a normal search. commit before the late submission deadline will be accepted and that late. In this assignment, for the sake of simplicity, you will only use the Y-coordinates of the right hand and the right thumb to construct your HMM. Learning provides a valuable approach that suggests not solving the problem directly but by indirectly teaching a program to learn faces via techniques of unsupervised and supervised learning. Doing so will count as violating the honor code. Assume the following variable conventions: Assume that each team has the following prior distribution of skill levels: In addition, assume that the differences in skill levels correspond to the following probabilities of winning: You can check your network implementation in the command line with. Now you will implement the independent Metropolis-Hastings sampling algorithm in MH_sampler(), which is another method for estimating a probability distribution. Takes, #this function not needed for skid variantc - not used, Clears the laser made in the previous move, Function to play out a move history on a new board. The temperature gauge reads the correct temperature with 95% probability when it is not faulty and 20% probability when it is faulty. See which player is inactive. We recognize this is a hard assignment and tri-directional search is a more research-oriented topic than the other search algorithms. str: Name of the player who's actively taking a turn. How should we compare if an observation if closer to one state or another? move_history: [(int, int)], History of all moves in order of game in question. If you followed the setup instructions exactly, then you should activate your conda environment using conda activate
from the Anaconda Prompt and start Jupyter Notebook from there. git clone https://github.gatech.edu/omscs6601/assignment_2.git Activate the environment you had created during Assignment 0: conda activate ai_env In case you used a different environment name, to list of all environments you have on your machine you can run conda env list. Don't worry about the probabilities for now. This page is my learning summary of Georgia Tech's Artificial Intelligence course, CS 6601, taken in Fall 2012. You signed in with another tab or window. In this assignment, you will work with probabilistic models known as Bayesian networks to efficiently calculate the answer to probability questions concerning discrete random variables. CS6100 (AI) lectures, assignments (Git) and the book are all available online, hence it is highly recommended to start early with assignments 1 and 2 which are huge time sinks. You can return the path in any order. sign in Which algorithm converges more quickly? Please run: You will get autogenerated submission/submission.py file where you can write your code. Metropolis Hastings Sampling - 1 return this with this function etc.- about 750 lines total, so at least half of that is like comments / function declarations to use Codespaces. Search is also the basis of more advanced AI techniques, such as simulated annealing, genetic algorithms, two-player zero-sum games (including games with chance), and constraint satisfaction problems. https://github.com/jpermar/gt6601learningportfolio/blob/master/papers/paper1.pdf, https://github.com/jpermar/gt6601learningportfolio/blob/master/papers/paper2.pdf. There was a problem preparing your codespace, please try again. I completed two projects, one on search in two-player zero-sum games, and other on gesture recognition. Hint 2: Example: Say 46 is the rightmost observation in State 1. will be based on Atlanta Pickle data. In Part 1a, we use only right-hand Y-axis coordinates as our feature, and now we are going to use two features - the same right-hand Y-axis coordinates and the right-thumb Y-axis coordinates. However, the alarm is sometimes faulty. You have just completed your final assignment for CS6601 Artificial Intelligence. As such, during grading, we will evaluate your performance on the map of Romania included in this assignment. Please use your submissions carefully and do not submit until you have thoroughly tested your code locally. Skip to content Toggle navigation. You signed in with another tab or window. The philosophical underpinnings of modern AI are rationality, vaguely defined as seeking a "best outcome" given goals and knowledge of the world. From the reading and assignments alone, I learned the conceptual and mathematical underpinnings of modern AI. Lecture 5 on Probability A key idea behind using logic is to enable entailment of new facts from existing knowledge, resulting in a learning capability for agents able to sense their environment. Are you sure you want to create this branch? A tag already exists with the provided branch name. The following exercises will require you to implement several kinds of bidirectional searches. The fourth assignment tested our knowledge of 1) deterministic planning by creating a sequence of actions in PDDL that lead from an initial world state to a goal state and 2) probabilistic inference using Bayesian networks. Many previous students have found it useful to go through the resources in this README if they are having difficulty understanding the algorithms. Depending on your changes, the auto grader might face difficulties while testing. As a result, when you run the bidirectional tests in search_submission_tests.py, it generates a JSON file in the GeoJSON format. Sanity check for making sure a move isn't occupied by an X. bool: Whether the [row,col] position is blank (no X), Sanity check for checking if a spot is occupied by a player, bool: Whether the [row,col] position is currently occupied by a player's queen, Sanity check to see if a space is within the bounds of the board and blank. ", "gauge" (high = True, normal = False), "temperature" (high = True, normal = False), the marginal probability that the alarm sounds, the marginal probability that the gauge shows "hot", the probability that the temperature is actually hot, given that the alarm sounds and the alarm and gauge are both working. If nothing happens, download GitHub Desktop and try again. str: Name of the player who's waiting for opponent to take a turn. CS 6601: Artificial Intelligence - Assignment 2 - Search. random.randint() or random.choice(), for the probabilistic choices that sampling makes. and your file will be created under the submission directory. 3 total matches are played. Each move takes the form of (row, column). This slide deck There is simply no comparison between reading the book on your own and learning the concepts and techniques presented in the lectures. Hint: Should pass in yourself to get your moves. Cannot retrieve contributors at this time. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. When nodes in the priority queue have the same priority value, break ties according to FIFO. Cannot retrieve contributors at this time. and then save the file. Part 2a: Multidimensional Output Probabilities, [Required for CS6601: 6 Points][Extra Credit for CS3600: 3 Points], [Required for CS6601: 39 Points][Extra Credit for CS3600: 7 Points], CS6601 CS3600 Assignment 6 Hidden Markov Models, Isolated Sign Language Recognition Corpus, 31, 28, 28, 37, 68, 49, 64, 66, 22, 17, 53, 73, 81, 78, 48, 49, 47, -4, 69, 59, 45, 62, 22, 17, 28, 12, 14, 24, 32, 39, 61, 35, 32, 45, 68, 62, 75, 61, 44, 73, 72, 71, 75, 55, 33, 33, 32, 32, 34, 38, 43, 41, 35, 36, 36, 37, 38, 38, 39, 40, 38, 38, 33, 31, 29, 28, 25, 24, 25, 28, 28, 38, 37, 40, 37, 36, 36, 38, 44, 48, 48, 22, 17, 18, 35, 33, 36, 42, 36, 41, 41, 37, 38, 38, 37, 35, 32, 35, 13, 36, 41, 41, 31, 32, 34, 34, Canvas Lectures on Pattern Recognition Through Time (Lesson 8), We have provided a copy of the Wikipedia page that has been edited for the benefit of this assignment, the transition probabilities of each state, the mean & standard deviation of emission Gaussian distribution of each state. 2. Assignment 5 for intro to AI - K-means and Gaussian Mixture models. - This means you can submit a maximum of 5 times during the duration of the assignment. Use the VariableElimination provided to perform inference. use get_active_moves or get_inactive_moves instead. These questions were answered in our second assignment. You will be implementing game playing agents for a variant of the game Isolation. Please explain what's happening in the code and why the line below is needed or if it could be. We are also implementing this through Jupyter Notebook, so you all may find it useful to spend some time getting familiar with this software. The last submission before the deadline will be used to determine your grade. Use Git or checkout with SVN using the web URL. In your Gradescope submission history, you can mark a certain submission as 'Active'. The assignments effectively picked up where the reading left off. Are you sure you want to create this branch? The submission marked as Active in Gradescope will be the submission counted towards your grade. What have you learned? Spring 2020, CS 6601 Note: DO NOT USE the given inference engines or pgmpy samplers to run the sampling method, since the whole point of sampling is to calculate marginals without running inference. For example, to connect the alarm and temperature nodes that you've already made (i.e. The easiest way to do this is through pip: After the clone, we recommend creating a branch and developing your agents on that branch: (assuming develop is the name of your branch). This is the heart of the assignment. # 'C1': .083, 'C2': 0, 'C3': 0, 'C4': 0, 'C5': 0, 'C6': 0, 'C7': 0, 'Cend': 0, # 'L1': .667, 'Lend': .083, 'W1': 0, 'Wend': 0. The best alternative is to create your own data structure(s). How was Compilers considering workload and difficulty? Ans: You may have run a cell that modifies that variable too many times. If you sort the neighbors alphabetically before processing them, you should return the same number of explored nodes each time. Bidirectional A star example method 1.pdf, Bidirectional A star example method 2 using 4th edition book.pdf, Search Question solutions + Partial credit explanation.pdf, AI Logic&PlanningWithAnswers - Spring2022.pdf, Game-Playing-Final-Solutions-CS6601-Q1.pdf, Midterm_v1.0_SPRING2020_Clarifications.pdf. assuming that temperature affects the alarm probability): Use function BayesNet.add_edge(,). This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. The pgmpy package is used to represent nodes and conditional probability arcs connecting nodes. During lecture, Thad provides his own perspective on the techniques, which typically differs from the book material. 20%). The goal here will be to use the HMM derived from Part 1a (states, prior probabilities, transition probabilities, and parameters of emission distribution) to build a Viterbi trellis. For the main exercise, consider the following scenario. In Part 1 you will build a one dimensional model, recognizing words based only on a series of right-hand Y coordinates; in Part 2 you will go multidimensional and utilize both the right hand and the right thumb features. Round the values to 3 decimal places thoughout entire assignment: Those values can be hardcoded in your program. Get position of certain player object. to completely compute the distribution. It should do better than the naive implementation in our tests (InsertionSortQueue), which sorts the entire list after every insertion. A tag already exists with the provided branch name. Implement bidirectional A* search. # 'C1': .036, 'C2': 0, 'C3': 0, 'C4': 0, 'C5': 0, 'C6': 0, 'C7': 0, 'Cend': 0, # 'L1': 0, 'Lend': 0, 'W1': .857, 'Wend': .036, sequence: a string of most likely decoded letter sequence (like 'A B A CAC', using uppercase). This way, when you print counter, you get counter = 1, right? Do not, # add any classes or functions to this file that are not part of the classes, evidence_vector: A list of dictionaries mapping evidence variables to their values, prior: A dictionary corresponding to the prior distribution over states, states: A list of all possible system states, transition_probs: A dictionary mapping states onto dictionaries mapping states onto probabilities, emission_probs: A dictionary mapping states onto dictionaries mapping evidence variables onto, sequence: A list of states that is the most likely sequence of states explaining the evidence, like, # pseudocode from https://en.wikipedia.org/wiki/Viterbi_algorithm modified to use log probability, # get most probable state and its backtrack, # follow the backtrack till the first observation. There are three frisbee teams who play each other: the Airheads, the Buffoons, and the Clods (A, B and C for short). executable file 62 lines (35 sloc) 2.87 KB Raw Blame Setup Clone this repository recursively: git clone --recursive https://github.gatech.edu/omscs6601/assignment_4.git (If your version of git does not support recurse clone, then clone without the option and run git submodule init and git submodule update ). You signed in with another tab or window. N could typically take values like 10,20,,100 or even more. The remainder of the assignment covered probability, and the critically important and pervasive Bayes' rule, which is the basis for Bayesian networks and probabilistic inference. Implement custom_search() using whatever strategy you like. Used to initialize board copy. Show the flowchart and code. In a typical ASL recognition system, you observe the XY coordinates of the speaker's left hand, right hand, and nose for every frame. (If your version of git does not support recurse clone, then clone without the option and run git submodule init and git submodule update). Please report this error to Product Feedback. Automate any workflow . To use this option run the following commands in the root directory of your assignment: Your code lives in the /vagrant folder within this virtual machine. There were two mini-projects in which I chose to research a problem that was supposed to be relevant to my your future career. Now try running counter += 1 again, and now when you try to print the variable, you see a value of 2. Ans: This is one thing that is very different between IDEs like PyCharm and Jupyter Notebook. All words must start from State 1 and can only transit to the next state or stay in the current one. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. sign in Data README.md README.md CS6601 The sixth assignment, Learning, focused in on two common and powerful techniques for learning from data: learning decision trees from a data set via information gain and designing a neural network for XOR, which taught me exactly how neural networks can learn: by modifying weights on linked units, each of which implements a threshold functions. to use Codespaces. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. This method should just perform a single iteration of the algorithm. - You may find this helpful in understanding the basics of Gibbs sampling over Bayesian networks. Learn more. You will build a word recognizer for American Sign Language (ASL) video sequences. Useful for testing purposes; call board.play_isolation() afterwards to play, board_state: list[str], Desired state to set to board, p1_turn: bool, Flag to determine which player is active, # set last move to the first found occurance of 'Q1', # Count X's to get move count + 2 for initial moves, #function to edit to introduce any variant - edited for skid variant by Aoun Hussain (1/28/2022), Apply chosen move to a board state and check for game end, queen_move: (int, int), Desired move to apply.
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