[CT421]: Assignment 2 submission
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year4/semester2/CT421/assignments/assignment2/submission.zip
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../latex/CT421-Assignment-02.pdf
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# `ipd.py`
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## Dependencies
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The program doesn't use any dependencies other than Python itself, so as long as you have Python installed, you're good to go.
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## Usage
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Run the program using `python ipd.py -h` for the following usage information:
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```
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usage: ipd.py [-h] [-s SIZE] [-g NUM_GENERATIONS] [-a GIVE_UP_AFTER]
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[-i NUM_ITERATIONS] [-p SELECTION_PROPORTION]
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[-c CROSSOVER_RATE] [-m MUTATION_RATE] [-o OUTPUT_FILE]
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[-n NOISE_LEVEL]
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Program to evolve strategies for the Iterated Prisoner's Dilemma
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options:
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-h, --help show this help message and exit
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-s, --size SIZE Initial population size
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-g, --num-generations NUM_GENERATIONS
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Number of generations
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-a, --give-up-after GIVE_UP_AFTER
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Number of generations to give up after if best
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solution has remained unchanged
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-i, --num-iterations NUM_ITERATIONS
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Number of iterations of the dilemma between two agents
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-p, --selection-proportion SELECTION_PROPORTION
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The proportion of the population to be selected
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(survive) on each generation
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-c, --crossover-rate CROSSOVER_RATE
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Probability of a selected pair of solutions to
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sexually reproduce
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-m, --mutation-rate MUTATION_RATE
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Probability of a selected offspring to undergo
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mutation
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-o, --output-file OUTPUT_FILE
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File to write TSV results to
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-n, --noise-level NOISE_LEVEL
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The probability that the opponent's last move will be
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misrepresented to the agent
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```
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An example run of the program with default values would simply be `python ipd.py`.
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To change the fitness function used, comment / uncomment lines in the list of possible strategies in the `fitness()` function.
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year4/semester2/CT421/assignments/assignment2/submission/ipd.py
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year4/semester2/CT421/assignments/assignment2/submission/ipd.py
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../code/ipd.py
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../code/plots.py
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