Evolving Referential Communication in Embodied Dynamical Agents Paul L. Williams 1 , Randall D. Beer 1,2,3 and Michael Gasser 1,2 1 Cognitive Science Program, 2 Dept. of Computer Science, 3 Dept. of Informatics Indiana University, Bloomington, IN 47406 USA plw@indiana.edu Abstract This paper presents results from three experiments which in- vestigate the evolution of referential communication in em- bodied dynamical agents. Agents, interacting with only sim- ple sensors and motors, are evolved in a task which requires one agent to communicate the locations of spatially distant targets to another agent. The results from these experiments demonstrate a variety of successful communication strate- gies, providing a first step towards understanding the emer- gence of referential communication in terms of coordinated behavioral interactions. Introduction Communication is traditionally viewed as the use of signals to transmit information (Hauser, 1997; Seyfarth and Cheney, 2003; Smith and Harper, 1995). We refer to this view of communication as the IT view, for information transmis- sion. Numerous models of emergent communication adopt this view as their starting point (Cangelosi and Parisi, 1998; MacLennan and Burghardt, 1993; Steels, 2003). Agents are provided with signalling mechanisms and informational content (or “meanings”), and through some adaptive pro- cess they establish shared associations between signals and meanings. However, the IT view of communication is not uncontroversial (Di Paolo, 1997, 1998), providing motiva- tion to study emergent communication without preconceived notions of signals and information transmission. Moreover, even if the IT view is accepted, models that begin with es- tablished signalling mechanisms cannot be used to address important questions of how signals may arise from initially non-communicative behaviors. An alternative view of communication comes from au- topoetic theory (Maturana, 1978; Maturana and Varela, 1980), with similar ideas expressed by researchers in cy- bernetics, psychology, and a wide range of other disciplines (see Di Paolo (1997) for an extended discussion). On this view, communication occurs whenever the behavior of one agent shapes the future behavior of another agent. Thus, communication is taken to refer to all kinds of socially coor- dinated behaviors. We refer to this view of communication as the CB view, for coordinated behavior. Importantly, the CB view does not assume the existence of signals or infor- mation transmission as fundamental aspects of communica- tion. Rather, if anything, these ideas are left to the analysis of communication by scientific observers. The essential ele- ments of communication are the structured interactions that take place between agents in a shared domain. Several models have explored the emergence of commu- nicaton from a CB perspective (Baldassarre et al., 2003; Di Paolo, 2000; Iizuka and Ikegami, 2003; Nolfi, 2005). In these models, agents are typically equipped with dedicated channels to use for communication. Through some adaptive process, the agents develop the ability to use these channels to signal each other, resulting in the improved coordination of their behaviors. Thus, since these models begin with- out pre-specified signals, they provide compelling demon- strations of how initially non-communicative behaviors can adapt to serve communicative functions. This is particu- larly true when agents are equipped with only sensors and actuators, and without dedicated communication channels (Quinn, 2001; Quinn et al., 2003). In this case, simulations can provide additional insights into the interplay between communicative and non-communicative behaviors, and ex- plore how signals may emerge from behaviors that initially evolved for other purposes. Models that study communication from the CB perspec- tive have typically focused on certain kinds of tasks. For instance, common tasks are those which require agents to develop signals for the dynamic assignment of roles (e.g. “leader” and “follower”) in some situation. In contrast, models of communication from an IT perspective have of- ten studied tasks that are referential in nature, where agents must develop signals that refer or “point to” states of affairs that are removed in space and/or time. Referential tasks are certainly of principal importance for understanding the evo- lution of communication, but to our knowledge no such tasks have been addressed within a CB framework. Accordingly, referential communication provide an important challenge for models of communication based on a CB perspective. In this paper, we present results from a series of experi- ments which explore the evolution of referential communi- Artificial Life XI 2008 702