About CS 2510 A

An introduction to artificial intelligence including logic and rule-based approaches, heuristic search, A*, IDA*, minimax, alpha/beta pruning, expectiminimax, Markov models and MDPs, decision tree, ensemble learning / random forest, the neural model and simple multi-layer perceptrons. Other topics, if any may vary. Prerequisite: C- or better in CS 2240.

Notes

Prereqs enforced by the system: CS 2240; Open to both Degree and PACE students

Section Description

An introduction to artificial intelligence including logic and rule based approaches, heuristic search, A*, IDA*, minimax, alpha/beta pruning, expectiminimax, Markov models and Markov decision processes (MDPs), decision tree, ensemble learning / random forest, the neural model and simple multi-layer perceptrons. Other topics, if any, may vary.

Section Expectation

Prior knowledge of material from CS 1640 Discrete Structures (or equivalent) and CS 2240 Data Structures and Algorithms. CS2240 prerequisite (but instructor permission not required)

Evaluation

Weekly quizzes, frequent active learning exercises, occasional homework (4--6 over semester), midterm and final.

Important Dates

Last Day to Add
Last Day to Drop
Last Day to Withdraw with 50% Refund
Last Day to Withdraw with 25% Refund
Last Day to Withdraw

Resources

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