Chapter 12: Putting It All Together

Over the previous eleven chapters, we've looked at various AI methods and built some simple demo applications using Unity3D. In this final chapter, we'll develop a more complex game example using some of the techniques we explored in previous chapters. The techniques we'll be using in this chapter include navigation meshes and finite-state machines (FSMs), but, more importantly, we will learn how to navigate and add AI to a pre-existing complex game. So, unlike the other chapters, this example is more like a real-world scenario.

In this chapter, we'll add AI to a simple tank combat game called TANKS! and contained in one of the official Unity tutorials, which, in turn, was inspired by an historic tank game called Combat for the Atari 2600. In the default version, TANKS! is a two-player game. Each player takes control of a tank, and the goal is to destroy each other. To make things more complicated, the player can decide the...

Technical requirements

For this chapter, you just need Unity3D 2022. You can find the example project described in this chapter in the Chapter 12 folder in the book's GitHub repository: https://github.com/PacktPublishing/Unity-Artificial-Intelligence-Programming-Fifth-Edition/tree/main/Chapter12.

Developing the basic game structure

For this demo, we will write an AI for the free tutorial game TANKS!. You can download the base game from Unity Asset Store (https://assetstore.unity.com/packages/essentials/tutorial-projects/tanks-tutorial-46209), or follow along with the version included in the Chapter 12 folder of this book's GitHub repository. The version included with this book has the advantage of already having been tested for Unity 2022.

In either case, the game is the same. When we start the game, we see a pleasant desert scenario, with rocks, structures, palm trees, and so on. Using the keyboard, we should be able to control the blue tank (the tank moves with W, A, S, and D and shoots with the Spacebar).

The following screenshot shows the basic structure of the game:

Figure 12.1 – Basic hierarchy of the game

The first time you start with an existing project, spend as much time as you can familiarizing yourself with the game structure...

Adding automated navigation

The first step is to modify the level to support automated navigation. In the original game, the players control all the moving objects (the tanks), so pathfinding is unnecessary. Now that we want to add AI, we need to have a world representation through which the AI can move. Luckily, this process is straightforward, thanks to NavMeshes.

Creating the NavMesh

To do this, perform the following steps:

1. Open the Navigation window (Window | AI | Navigation) and look at the NavMesh generation parameters. In this case, NavMesh generation is relatively easy: we are only interested in moving around on the ground surface plane, so there are no jumps, no links, and no slopes we need to care of.
2. The only adjustment to the default NavMesh parameters we need to make is for the baking agent size (that is, the measures of the virtual agent used by Unity to verify whether a location is large enough to allow the Agent to pass).
3. The tanks used in the...

Creating decision-making AI with FSM

In Chapter 2, Finite State Machines, we saw how to implement a simple FSM. In this section, we are using the same technique, but will apply it to the more complex scenario of this demo.

First, we need an FSM plan. We are interested only in connecting the FSM to the existing game for this demo, so we will keep it simple. The FSM for our tank is composed of just two states – patrolling and shooting.

The plan is nice and straightforward:

1. The AI tank starts in the Patrol state and wanders around the previously defined patrolling points.
2. Then, if the players get in range, the tank switches to the Attack state.
3. In the Attack state, the tank turns toward the player and starts shooting at it.
4. Finally, if we are in the Attack state and the players leave the AI's range, the tank will return to the Patrol state.

Figure 12.8 – The simple FSM for the enemy tanks

For the implementation...

Summary

In this chapter, we applied some of the AI techniques that we learned previously to our simple tanks combat game. Then, of course, we'd be able to use some more techniques in a larger game scope. Still, in this short chapter, we reused the simple FSM framework that we built in Chapter 2, Finite State Machines, as well as Unity's built-in navigation meshes capabilities.

This example project is a perfect starting point for exploring the AI techniques introduced in this book. You can implement many more improvements to the AI of this demo, and I encourage you to play with it a bit more. There are several pieces of low-hanging fruit, so here are my suggestions:

As a first exercise, you can increase the number of states, for instance, by adding a Chasing state in which the tank will actively look for the player. This structure is like the Attack state, but with a bigger radius. Then, as a more significant step, try to replace the FSM with a Behavior tree. The Behavior...

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