In this project, your Pacman agent will find paths through his maze world, both to reach a particular location and to collect food efficiently. You will build general search algorithms and apply them to Pacman scenarios.
In this project, you will design agents for the classic version of Pacman, including ghosts. Along the way, you will implement both minimax and expectimax search and try your hand at evaluation function design.
CS 188 Introduction to Artificial Intelligence
🤖Artificial Intelligence - Berkeley - CS188 - Summer 2016
Artificial Intelligence, UC Berkeley's CS188 taught at ShanghaiTech
I have completed four Pacman projects of the UC Berkeley CS188 Intro to Artificial Intelligence course. The Pac-Man projects were developed for CS 188. They apply an array of AI techniques to playing Pac-Man. They teach foundational AI concepts, such as informed state-space search, probabilistic inference, and reinforcement learning.
👻 UC Berkeley CS188 Intro to AI -- The Pac-Man Projects
Tutorials & Projects from CS188 Introduction to AI (UCB) & COMP90054 AI Planning for Autonomy (UniMelb)
The Pac-Man Projects from UC Berkeley Introduction to Artificial Intelligence course (CS188)
Implementation of projects 0,1,2,3 of Berkeley's AI course
My solutions to projects 1, 2 & 3 of Berkeley's AI course
Explore foundational AI concepts through the Pac-Man projects, designed for UC Berkeley's CS 188 course. Implement search algorithms, multi-agent strategies, and reinforcement learning techniques in Python, emphasizing real-world applications. Engage in the Eutopia Pac-Man contest for a multiplayer capture-the-flag challenge
In this repository, I outline the course lab carried out for the Artificial Intelligence CSE 4617 course along with the lab CSE 4618, conducted by Bakhtiyar Hasan Sir Note: We did not have to implement all of the code but rather portions of the code as outlined by the taskbook in the resources section
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