eddie-z/artificialintelligence310

CMPT310_PACMAN:
Objective:
-Implement BFS, DFS for depthFirstSearch and breadthFirstSearch functions.
-Implement A* graph search in the empty function aStarSearch in search.py.
-Implement the CornersProblem search problem in searchAgents.py.
-Implement a heuristic for the CornersProblem in cornersHeuristic.
Results:
Using commands in terminal:
-python pacman.py -l tinyMaze -p SearchAgent.
-python pacman.py -l mediumMaze -p SearchAgent.
-python pacman.py -l bigMaze -z .5 -p SearchAgent.
Shows:
The Pac-Man board will show an overlay of the states explored, and the order in which they were explored (brighter red means earlier exploration).

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CMPT310_DPLL:
Objective:
-Complete the empty function toCNF in sudoku.py. The function toCNF takes three arguments: the number N, an instance of sudoku of size NxN, and a string (for the name of output file).

Implement unit propagation for propagate-units(F).
Implement pure elimination for pure-elim(F).
Implement recursive backtracking for solve(var,F).

Results:
Using commands in terminal:
python sudoku.py -n 3 -i sudoku3_unsat.txt
python sudoku.py -n 5
python sudoku.py -n 9 -i sudoku9.txt

python DPLLsat.py -i

Shows:
Correctly generated:
sudoku3_unsat.txt3.cnf
5.cnf
sudoku9.txt9.cnf

Program should print “UNSAT” if a formula is unsatisfiable and "SAT" if it is satisfiable.

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CMPT310_ECOLI:
Objective:
Implement HMM.logprob() calculates the probability of a particular sequence of states and characters.
Implement HMM.viterbi() uses the Viterbi algorithm to calculate the most likely sequence of states given a sequence of DNA characters.

Results:
Using commands in terminal:
python a3_template.py "small.txt"
python a3_template.py "ecoli.txt"

Shows:
E. coli output named ecoli_output.txt.

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CMPT310_HMM
Objective:
Implement compute_activations.
Implement backpropgration.

Results:
Using commands in terminal
python digit_classification.py --mode=test --model=model-20190328-164647.pkl

Shows:
Displays number.