{"id":21421420,"url":"https://github.com/percival33/introduction-to-ai","last_synced_at":"2025-10-04T10:31:56.938Z","repository":{"id":107184965,"uuid":"601800360","full_name":"Percival33/Introduction-to-AI","owner":"Percival33","description":"Introduction to Artificial Intelligence - academic course laboratory problems","archived":false,"fork":false,"pushed_at":"2023-02-14T21:15:00.000Z","size":2391,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-11-22T20:37:25.085Z","etag":null,"topics":["ml","python"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Percival33.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-02-14T21:07:12.000Z","updated_at":"2023-02-14T21:45:27.000Z","dependencies_parsed_at":null,"dependency_job_id":"90e457c8-b35b-44f1-b8e9-7581b082cebe","html_url":"https://github.com/Percival33/Introduction-to-AI","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Percival33%2FIntroduction-to-AI","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Percival33%2FIntroduction-to-AI/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Percival33%2FIntroduction-to-AI/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Percival33%2FIntroduction-to-AI/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Percival33","download_url":"https://codeload.github.com/Percival33/Introduction-to-AI/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":235239037,"owners_count":18958087,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ml","python"],"created_at":"2024-11-22T20:34:11.473Z","updated_at":"2025-10-04T10:31:51.493Z","avatar_url":"https://github.com/Percival33.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# WSI_22Z\n\nIntroduction to Artificial Intelligence - academic course\n\n### Table of contents\n\n- [lab_1.1](#lab_1.1) - Search Space vol. 1\n- [lab_1.2](#lab_1.2) - Search Space vol. 2\n- [lab_2](#lab_2) - Evolutionary and Genetic Algorithms\n- [lab_3](#lab_3) - Deterministic two-player games\n- [lab_4](#lab_4) - Regression and Classification\n- [lab_5](#lab_5) - Artificial neural networks\n- [lab_6](#lab_6) - Reinforcement learning (RL)\n- [lab_7](#lab_7) - Bayesian Models\n\n## lab_1.1\n\n_Search Space - Knapsack problem_\n\n**Task:**\n\nFind the optimal solution by exhaustive search. Solve the problem using a heuristic: pack items into a backpack in order of decreasing value-to-weight ratio.\n\n## lab_1.2\n\n_Search Space - Stochastic Gradient Descent_\n\n**Task:**\n\nPlease implement the steepest descent/ascent method. We calculate the gradient numerically. Apply the method to find the minimum of the Booth function in 2 dimensions, then to find the minimum of functions 1 to 3 from CEC 2017 in 10 dimensions.\n\n## lab_2\n\n_Evolutionary and Genetic Algorithms - evolutionary algorithm_\n\n**Task:**\n\nImplement a classic evolutionary algorithm without crossover, using tournament selection and elitist succession. The available budget is 10000 evaluations of the objective function. We are optimizing functions number 4 and 5 from CEC 2017 in 10 dimensions. The bounds of the search space are -100 and 100.\n\n## lab_3\n\n_Deterministic two-player games - MiniMax checkers_\n\n**Task:**\n\nImplement the alpha-beta pruning min-max algorithm and apply it to the game of checkers/draughts. Let the evaluation function return the difference between the player's and the opponent's board state.\n\n## lab_4\n\nRegression and Classification - ID3 algorithm\n\n**Task:**\n\nImplement the ID3 classifier (decision tree) with nominal attributes and identity tests. Provide accuracy and confusion matrices for given datasets.\n\n## lab_5\n\n_Artificial neural networks - two-layer perceptron_\n\n**Task:**\n\nImplement a two-layer perceptron and train it to represent the function `J: [-5,5] → R`, given by the formula: `J(x) = sin(xsqrt(5))+cos(xsqrt(3))`.\n\n## lab_6\n\n_Reinforcement learning (RL) - Qlearning agent_\n\n**Task:**\nImplement the Q-Learning algorithm and use it to determine a decision policy for the FrozenLake8x8 problem.\n\nIn addition to investigating the default reward system (1 for reaching the goal, 0 otherwise), please propose your own system of rewards and penalties, and then compare the results achieved with the default system.\n\n## lab_7\n\n_Bayesian Models - Random data generator using Bayesian network distribution_\n\n**Task:**\n\nImplement a random data generator that follows the distribution represented by a given Bayesian network. The network describes the dependencies between (binary) random variables and is provided as a graph structure and conditional probability tables in a text file. Divide the generated set and use it to train and test the classifier created in previous exercises.\n\n### How to get CEC functions?\n\n```\ngit clone https://github.com/tilleyd/cec2017-py\ncp -R cec2017-py/cec2017 .\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpercival33%2Fintroduction-to-ai","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpercival33%2Fintroduction-to-ai","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpercival33%2Fintroduction-to-ai/lists"}