Artificial Intelligence Pacman

● Utilized Depth first search, Breadth first search, Uniform cost search, and A* search to assist pacman finding the most optimal pathway to consume all food on the board

● Created smart heuristic functions to estimate the distance of an agent's current state to the goal state

● Designed multiple agents to help both Ghost and Pacman make decisions on their turn, using Expectimax and Minimax with alpha beta pruning

● Implemented smart evaluation function that evaluates how good a current state is for an agent

Language Detector

● Created a Node Application that made use of ExpressJS

● Made use of google translation API for the language detection of any phrases

● Deployed the website onto the web using cyclic

● Utilized MongoDB to store users entered phrases

Ocaml Interactive Console

● Developed a lexer that takes in strings such as Ocaml expressions and converts them into a list of tokens

● Developed a parser that takes in a list of tokens created by the lexer and converts that into an Abstract Syntax Tree

● Developed an interpreter that uses the lexer and parser to evaluate expressions and interact using Ocaml logic