Lab 11: Predator/Prey Simulation

The goal of this lab is to experiment with a biological simulator, and especially how polymorphism is useful in its design.

1. Setup and introduction

As in previous assignments, move into your cs235 directory. Then clone the repository for this lab and move into the new lab11 directory.

hg clone /cslab/class/csci235/lab11
cd lab11

If you do ls -F, you'll see an item simulation, which is a directory containing the source code for the simulation package, which contains the grid and windows. You will not need modify any of this, but you may look at it if you're curious.

You will be working with various implementations of the Agent interface. In addition to what is in that interface, you need to know a few public methods on the SimulationGrid class:

• boolean isOccupied(int xPos, int yPos)
• boolean isOpen(int xPos, int yPos)
• Agent getAgentAt(int xPos, int yPos)
• void setAgentAt(int xPos, int yPos, Agent a)

Conveniently, the first three of these will do the right thing when you pass them a position that is outside the grid: both isOccupied() and isOpen() return false, and getAgentAt() returns null. You must, however, be sure that your xPos, yPos is in-bounds when you call setAgentAt().

2. Initial experiments

The first thing you should do is glance over the code to familiarize yourself with it. This version of the simulator is similar to what you saw in class for the Life game. In the Life version, every cell in the grid was occupied by an agent; every agent stayed in the cell in which it was created; and each step of the simulation first invoked plan() for all of the agents, then step(), so that all of the agents acted simultaneously. This version changes all of those: some cells are unoccupied (so that getAgentAt() returns null), some of the species move from cell to cell, and each step of the simulation calls a single act() once for each agent. The agents therefore move one after another, with each getting one chance to act in each round.

Compile PredPrey.java and the species files. (Note: You will get a warning message about "unchecked or unsafe operations" when you compile any of your species. You may ignore that.) Now run the simulation. You can select between a small view or big view, by using the -small and -big flags, as in

java PredPrey -big &

The big view gets you a world that is 180x120 cells; the small view's world is 60x30.

Try running the simulation with various initial populations. If you observe that either foxes or rabbits have a particular advantage (say, foxes always eat all the rabbits before the rabbits eat all the clover, or if clover always becomes extinct), then you can adjust the reproductive threshold, speed, or visual acuity of one or more species to try to put them on more equal footing. Try to find an initial setup where you cannot predict the outcome--- where the outcome partially depends on the random placement and movement on the agents; for example, you might find that with 100 clover, 20 rabbits, and 5 foxes, sometimes the rabbits will become extinct, and other times the clover becomes extinct.

Take notes regarding your observations about the patterns of behavior. If you notice any peculiarities, can you explain why they happen? Can you think of a way to eliminate any oddities?

3. Experimental changes

Now you and your partner should think about what major changes you would like to make to the system to make it more interesting. (And don't forget that you can use hg commit to save the state and hg revert to back out of unhappy experiments.) Some obvious directions include the following:

• Add new species to the simulation. Possibilities include a super-predator which eats both rabbits and foxes; an omnivore which eats both clover and rabbits; another plant to compete with clover; another herbivore to compete with rabbits; another carnivore to compete with foxes.

  Once you compile a new subclass of Agent in your directory, that class will automatically show up in the initial-population dialogue when the simulator starts.

• Let animals lose weight as the move, and starve if they fall below a certain weight. With this, one can greatly increase the abilities of a predator, since they have the threat of starvation working against them.
• Improve the algorithms for foxes and rabbits for finding prey and/or eluding predators. The rabbits should go for the nearest clover and put a priority on escaping a predator (unless it is about to starve). A fox could be made to "remember" what rabbit it is chasing, or at least always head for he closest one Foxes also could be made to collude with one another (favor going after a rabbit that is close to another fox, so that together the foxes could trap it); in that case, you could program it so the foxes can share the rabbit (divide the weight among them).
• Growth rate, visual acuity, and speed can be instance variables, and difference instances (individuals) within the same class (species) can have different values. For example, when a new rabbit is made, its visual acuity could be randomly chosen to be one less than, equal to, or one greater than its parent's visual acuity. If you take this route, you should have some way to tell abilities of individuals within the simulation; for example, you could have an instance's color depend on its abilities, or at each cycle you could print to the screen the abilities of the currently surviving individuals.

The Java documentation includes a list of pre-defined color names that are available after importing java.awt.color.

Some ideas that students have come up with in the past:

• Putting a lifespan on agents, so they die after a certain number of cycles.
• Allowing the clover to spawn in random locations, as though they had wind-borne seeds)
• Adding a natural disaster to the simulation so that every so often a random portion of the island would be wiped out.
• Introducing seasons, so that every few cycles the island would switch between summer and winter, and the clover would grow only during the winter. (The clover would turn white during the winter, to make it easier to tell what season it was.)

When you have an idea, talk to me first so I can help you refine it and point you in the right direction on how to implement it.

As you try out your modified simulation, look for patterns of behavior. What parts seem to be realistic in modeling the real world? Can you make the system stable (no species becoming extinct, at least for a long time), or can you at least find a starting configuration where the results are unpredictable?

4. Report

Along with the code you wrote or modified, for this lab you should turn in a short report (a few paragraphs long). Talk about what you initially observed in the simulation before you modified it; what you wanted to change to make the simulation more realistic or interesting; what changes you made (including an explanation of the implementation and references to what part of the code you modified); and what you observed when running your new version of the simulation. You may write the report in a text file.

5. Turn-in

Turn in a hardcopy of your report.

In addition, turn in the .java source files for your species with a command like

/cslab/class/csci235/bin/handin lab11 Clover.java Rabbit.java Fox.java

Be sure to include any new species that you have added.