Cs 188 berkeley

This course will introduce the basic ideas and techniques underlying the design of intelligent computer systems.

Completed all homeworks, projects, midterms, and finals in 5 weeks. Created different heuristics. Helped pacman agent find shortest path to eat all dots. Created basic reflex agent based on a variety of parameters. Improved agent to use minimax algorithm with alpha-beta pruning. Implemented expectimax for random ghost agents.

Cs 188 berkeley

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Section 8 Recording Solutions. Artificial-Intelligence - Berkeley-CS

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This course will introduce the basic ideas and techniques underlying the design of intelligent computer systems. A specific emphasis will be on the statistical and decision-theoretic modeling paradigm. By the end of this course, you will have built autonomous agents that efficiently make decisions in fully informed, partially observable and adversarial settings. Your agents will draw inferences in uncertain environments and optimize actions for arbitrary reward structures. Your machine learning algorithms will classify handwritten digits and photographs. The techniques you learn in this course apply to a wide variety of artificial intelligence problems and will serve as the foundation for further study in any application area you choose to pursue. See the syllabus for slides, deadlines, and the lecture schedule. Readings refer to fourth edition of AIMA unless otherwise specified.

Cs 188 berkeley

This course will introduce the basic ideas and techniques underlying the design of intelligent computer systems. A specific emphasis will be on the statistical and decision-theoretic modeling paradigm. By the end of this course, you will have built autonomous agents that efficiently make decisions in fully informed, partially observable and adversarial settings. Your agents will draw inferences in uncertain environments and optimize actions for arbitrary reward structures. Your machine learning algorithms will classify handwritten digits and photographs. The techniques you learn in this course apply to a wide variety of artificial intelligence problems and will serve as the foundation for further study in any application area you choose to pursue. See the syllabus for slides, deadlines, and the lecture schedule. Readings refer to fourth edition of AIMA unless otherwise specified.

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Releases No releases published. Exam Prep 3 Recording Solutions. A specific emphasis will be on the statistical and decision-theoretic modeling paradigm. Skip to content. Moved pacman based on closest likely ghost location. Section 4 Recording Solutions. You signed out in another tab or window. Your machine learning algorithms will classify handwritten digits and photographs. Improved features used to distinguish digits. Folders and files Name Name Last commit message. Section 2 Recording Solutions. Created different heuristics. Finally, implemented joint particle filtering algorithm with multiple reactive ghosts. Section 9 Solutions. Section 6 Recording Solutions.

This course will introduce the basic ideas and techniques underlying the design of intelligent computer systems. A specific emphasis will be on the statistical and decision-theoretic modeling paradigm.

Project 4. Exam Prep 2 Recording Solutions. Improved pacman features. Ch Section 4 Recording Solutions. Project 3. Section 9 Solutions. Improved features used to distinguish digits. Exam Prep 14 Recording Solutions. Worked with Markov Decision Processes.