Description
You are introduced an electronic product that has a $value and a $price. Each product can be in a good condition, which works flawlessly, or in a Junk condition, where, hmm, it is junk. If you buy a product, and if it is good, your wealth increases by $value-$price. If, however, the product turns out to be Junk, your wealth decreases by $price. There are no returns! You do not know whether a product is good or Junk until you buy it; however, you are given the probability that it might be Junk. Your objective is to increase your agent’s wealth as much as possible.
You are provided two files:
* [agents.py](agents.py) contains the base Agent, a few other agents, and the StudentAgent that you need to implement.
* [simulate_agents.py](simulate_agents.py) contains the simulation code that simulates the provided agents and your agent under various conditions.
Your tasks are:
1. Modify the provided files as needed. See the comments in the Python files.
1. Run the simulate_agents.py file using “pyton simulate_agents.py > out.txt“ once your implementation is completed.
1. Submit your assignment (the Python files and the out.txt file) using git add, commit, and push commands as needed.
1. On Blackboard: submit a link to your github repository.
Note: your agent cannot cheat (i.e., simulate the markets, record the product conditions in a file, and read them later).
Points: 50.
Deadline: 10:00pm (Central US) on November 24th. The GitHub will automatically create a snapshot of your repository at 11:45pm. The standard late submission policy applies: 5-minute grace period; 1 point per late minute after 10:05pm.