# Automatic Design of Collective Behaviors for Robots that Can Display and Perceive Colors
## 2 Related Work
Few related studies have been conducted following the neuro-evolutionary approach [43; 44; 45; 46; 47]. [PERSON] et al. [43] evolved communication behaviors for a swarm performing a foraging mission. [PERSON] et al. [44] evolved self-assembly behaviors with a team of two robots. [PERSON] et al. [45; 46] evolved behaviors for coordinated motion with a group of three robots, and later, evolved a dynamic chain of robots that perform a foraging-like mission. [PERSON] and [PERSON] [47] used multi-objective optimization to evolve flocking and a two-robot collaborative behavior within a robot swarm. In the studies mentioned above, the methods under analysis have not been tested for their ability to generate control software autonomously. As a consequence, these studies belong in semi-automatic designrather than in automatic design [17]. Indeed, in these studies, researchers either focused a single mission [43; 44; 46] or modify the design methods and/or robot platform when they applied the methods under analysis to more than one [45; 47]. In addition, we argue that mission-specific bias was manually introduced in the way the robots display and perceive colors: robots display colors that are manually defined at the beginning of the experiment [44]; robots display color-based information that is encoded by the researchers [46; 47]; and the perception capabilities of the robots are adjusted to ease the emergence of a specific behavior [45; 46]. We contend that these studies do not expose the full potential of using color-based information in the automatic design of collective behaviors. As a matter of fact, previous works were limited to produce control software for robots than can display and perceive a single [43; 44; 45] or at most two simultaneous colors [46; 47]. Our research belongs in the family of modular design methods known as AutoMoDe [8]. In the rest of the section, we restrict our attention to this family. [PERSON] and [PERSON] [5] discussed how the capabilities of robot platforms limit the variety of collective behaviors that automatic design methods can produce. Methods conceived for e-puck robots with equal capabilities--such as Vanilla [8], Chocolate [9], Maple [10], Waffle [11], Coconut [12] and IcePop [13]--are restricted to address the same class of missions: robots in the swarm must position themselves regarding their peers [9; 15] or few static environmental features [8; 9; 10; 11; 12; 13; 15; 53], and they can only use a single global reference for navigation [8; 9; 10; 11; 12; 13; 15; 53]. In contrast, [PERSON] et al. [14] obtained a larger variety of collective behaviors by considering an extended set of capabilities with respect to those considered in Chocolate. They introduced Gianduja--a method for the automatic design of swarms of e-pucks that can selectively broadcast binary messages. [PERSON] et al. showed that by broadcasting and reacting to messages, the robots can perform missions that Chocolate cannot address--for example, missions that require event-handling collective behaviors. The approach we follow in our research is similar to the one of [PERSON] et al. [14]. We conceived TuttiFrutti as an instance of AutoMoDe that designs control software for e-pucks with the extended capability of communicating by displaying and perceiving colors. As we will see in Section 3, TuttiFrutti can address missions that require the robots to act according to color-based information--a class of missions that existing instances of AutoMoDe can not address.