Chapter 31. Enhancing Movement Behaviors with a Fuzzy System

Key Topics

• Fuzzy Variables and Membership Functions

• Fuzzy Rules

• Module Design

• Evaluation

It's clear that animats with simple obstacle avoidance will struggle in complex environments. To remedy this problem, fuzzy logic is used to craft behaviors necessary for dealing with contraptions—such as ladders, doors, and platforms. These capabilities are created by design, and are not acquired through learning. Other short sequences of actions would be equally as easy to create. Despite the focus on the three major contraptions, any other behavior discussed in the previous chapters could be implemented using an identical methodology.

Having a fallback is the main motivation for tackling the toughest behaviors first—particularly if the learning solution fails or takes too much time to develop for little benefit. This is good practice in a professional setting.

This chapter covers the following topics:

• The fuzzy variables involved both externally (interface to the problem) and internally (used by the solution), with an explanation of their membership functions when necessary

• Specific fuzzy rules for each of the behaviors, involving combinations of pressing buttons and moving forward

• The variables for climbing a ladder, using a door, and taking a platform

• The design of a simple fuzzy logic module to execute the rules, revealing the similarities between rule-based systems and fuzzy interpreters

• Minor flaws that cause idiosyncrasies in some rare cases, and possible improvements

At the end of this chapter, the artificial intelligence (AI) is enhanced to deal with a complex environment—still using reactive behaviors.