游戏AI代写 | Assignment 2: General Games – Part 1

本次澳洲代写是电子游戏的AI Frame相关的一个assignment

2 Assignment

This assignment uses the General Video Game AI framework (GVGAI). Detailed infor-
mation about the competition and GVGAI is given at http://www.gvgai.net/. You
have to use the framework to design and execute di erent game playing controllers. You
can get the code at https://github.com/GAIGResearch/GVGAI. You can only use
Java for this assignment.

Assignment 2 requires that you test existing controllers and develop and improve your
own controller based on techniques covered during this course. We only consider the
Single Player Planning Track in this assignment. For a quick start, take a look at
src/tracks/singlePlayer/Test.java for an example on how to use the framework.

In this assignment, we only consider games from Training Set 1 (http://www.gvgai.
net/training_set.php?rg=1). For each exercise, you have to evaluate the considered
controllers on the following 4 games: Aliens, Boulderdash, Butter ies, Chase. Note
that each game includes 5 levels (from \lvl0″ to \lvl4″), so you will be looking at 20 game
levels in total.

Exercise 1 Team work: who has done what? (zero points)

Just like in Assignment 1, we’d like each team member to write one paragraph about
what he or she has contributed to this assignment. We will not mark this, and it will not
have any e ect on the marking of the other exercises. You might now ask, \why do this
then?” { well, through this no-stakes approach, we’d like to encourage self-regulation
within the group and cooperative learning. You can’t lose; you can only win.

Exercise 2 Existing Controllers (30 points)

For this exercise, you have to run the existing controllers \Random”, \One Step Look-
Ahead”, and \Genetic Algorithm” available at http://www.gvgai.net/sampleControllers.
php.

1. Run each of the three controllers 10 times on each of the 5 levels of each game
(20 levels in total) and report for each game level the average score and standard
deviation.

2. Change the \One Step Look-Ahead” Controller such that it looks more than 1 step
ahead. Make sure that it does not exceed the time out and try to obtain a high
performing controller.

3. Run your new \several steps ahead”-controller on each game 5 times and report
the average score and standard deviation. In the report, you must brie y describe
and justify the changes that you have made.

Exercise 3 Genetic Algorithm Controller (20 points)

Consider the \Genetic Algorithm” Controller

1. Design an evolutionary algorithm to optimise the parameter setting (GAMMA,
SIMULATION DEPTH, POPULATION SIZE, RECPROB, MUT) for the \Ge-
netic Algorithm” Controller for all levels of a considered game (5 levels). The
objective is to maximise the scores this controller achieves on these games. In the
report, you must brie y describe the algorithm and justify its design.

2. Give the best obtained parameter settings for each of the 4 games together with
the results obtained for each game and compare it to the default parameter setting
tested in Exercise 2. The comparison should be statistically meaningful (i.e. using
statistical testing methods).


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