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Unity 5.x Game AI Programming Cookbook

You're reading from   Unity 5.x Game AI Programming Cookbook Build and customize a wide range of powerful Unity AI systems with over 70 hands-on recipes and techniques

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Product type Paperback
Published in Mar 2016
Publisher Packt
ISBN-13 9781783553570
Length 278 pages
Edition 1st Edition
Tools
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Authors (2):
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Jorge Palacios Jorge Palacios
Author Profile Icon Jorge Palacios
Jorge Palacios
Jorge Elieser P Garrido Jorge Elieser P Garrido
Author Profile Icon Jorge Elieser P Garrido
Jorge Elieser P Garrido
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Toc

Table of Contents (10) Chapters Close

Preface 1. Behaviors – Intelligent Movement FREE CHAPTER 2. Navigation 3. Decision Making 4. Coordination and Tactics 5. Agent Awareness 6. Board Games AI 7. Learning Techniques 8. Miscellaneous Index

Blending behaviors by priority

Sometimes, weighted blending is not enough because heavyweight behaviors dilute the contributions of the lightweights, but those behaviors need to play their part too. That's when priority-based blending comes into play, applying a cascading effect from high-priority to low-priority behaviors.

Getting ready

The approach is very similar to the one used in the previous recipe. We must add a new member variable to our AgentBehaviour class. We should also refactor the Update function to incorporate priority as a parameter to the Agent class' SetSteering function. The new AgentBehaviour class should look something like this:

public class AgentBehaviour : MonoBehaviour
{
    public int priority = 1;
    // ... everything else stays the same
    public virtual void Update ()
    {
        agent.SetSteering(GetSteering(), priority);
    }
}

How to do it...

Now, we need to make some changes to the Agent class:

  1. Add a new namespace from the library:
    using System.Collections.Generic;
  2. Add the member variable for the minimum steering value to consider a group of behaviors:
    public float priorityThreshold = 0.2f;
  3. Add the member variable for holding the group of behavior results:
    private Dictionary<int, List<Steering>> groups;
  4. Initialize the variable in the Start function:
    groups = new Dictionary<int, List<Steering>>();
  5. Modify the LateUpdate function so that the steering variable is set by calling GetPrioritySteering:
    public virtual void LateUpdate ()
    {
        //  funnelled steering through priorities
        steering = GetPrioritySteering();
        groups.Clear();
        // ... the rest of the computations stay the same
        steering = new Steering();
    }
  6. Modify the SetSteering function's signature and definition to store the steering values in their corresponding priority groups:
    public void SetSteering (Steering steering, int priority)
    {
        if (!groups.ContainsKey(priority))
        {
            groups.Add(priority, new List<Steering>());
        }
        groups[priority].Add(steering);
    }
  7. Finally, implement the GetPrioritySteering function to funnel the steering group:
    private Steering GetPrioritySteering ()
    {
        Steering steering = new Steering();
        float sqrThreshold = priorityThreshold * priorityThreshold;
        foreach (List<Steering> group in groups.Values)
        {
            steering = new Steering();
            foreach (Steering singleSteering in group)
            {
                steering.linear += singleSteering.linear;
                steering.angular += singleSteering.angular;
            }
            if (steering.linear.sqrMagnitude > sqrThreshold ||
                    Mathf.Abs(steering.angular) > priorityThreshold)
            {
                return steering;
            }
    }

How it works...

By creating priority groups, we blend behaviors that are common to one another, and the first group in which the steering value exceeds the threshold is selected. Otherwise, steering from the least-priority group is chosen.

There's more...

We could extend this approach by mixing it with weighted blending; in this way, we would have a more robust architecture by getting extra precision on the way the behaviors make an impact on the agent in every priority level:

foreach (Steering singleSteering in group)
{
    steering.linear += singleSteering.linear * weight;
    steering.angular += singleSteering.angular * weight;
}

See also

There is an example of avoiding walls using priority-based blending in this project.

You have been reading a chapter from
Unity 5.x Game AI Programming Cookbook
Published in: Mar 2016
Publisher: Packt
ISBN-13: 9781783553570
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