# Collective Memory: Transposing [PERSON]'s Experiment to Robot Swarms
## 5 Conclusions  
We introduced a novel collective behavior that allows groups to memorize simple information, although the individual members of the group do not use any memory. Instead of relying on the individuals, the information is encoded and stored in the spatial configuration of the group when it is aggregated. The seminal [PERSON] experiment was adapted to work with groups of robots, providing a simple and straightforward method to demonstrate the collective cognitive capability of memorizing information. We detailed a specific implementation of the behavior for a swarm of underwater robots, including a method to produce two different types of robot aggregates which represent a single bit of memory. This was achieved by dividing the group in two colored teams that can cluster in a mixed or in a segregated configuration. To put to use the information collectively stored, we introduced a local estimate, the recall coefficient that allows each individual member to form an opinion about the state of the collective memory. The whole group then processes all opinions with a quorum phase in which we have shown that all the robots converge to a collective decision that follows information stored in the collective memory. We have shown that the proposed behavior successfully recalls information in 82% of our repeated experiments (\(n=1000\)). The results show that, with relatively simple agents and simple behavioral rules, a group can have a memory of its own, independently of the internal state of its members. This first experiment is rather simple and involves a single bit memory to learn to associate two stimuli. There are several directions that may be considered to investigate how more information may be stored: it would be interesting to introduce more teams, and also multiple aggregation sites. Encoding more information may also be achieved with a larger palette of spatial configurations, but this might in turn involve higher individual complexity in order to create the configurations and to discriminate them effectively. Only with one aggregate, two basic mixed and segregated states, and three teams may we encode up to 12 different configurations. Another point of potential improvement is the accuracy of storing and recalling information. We suggest that mainly two aspects of the experiments can play a large role: first, the quality of individual perception because it directly impacts the ability of the robots to perceive their spatial configuration, and therefore what information is stored. Second, randomness that is inherent in this work (in particular when robots move using a random walk, and when they make a decision to remain stopped) will cause spatial configurations themselves to be less accurately defined. The impact of random events may strongly be reduced by working with larger group sizes. For instance, when segregated, a smaller fraction of the teams will perceive both colors. The collective behavior introduced in this paper may seem complicated for a task that is routinely achieved by most of the electronic devices in existence. However, we believe it bears significant interest in two cases: when the cost of implementing memory in an individual is high, for instance in synthetic biology with molecular machines and engineered bacteria, or in more elementary biochemical systems (to produce cognitive capabilities such as habituation or solve the detour problem), and when studying the behavior of groups with collective memory properties that may remain hidden when examining the individual members separately. Conceptualization: A.C. and J.-L.D. ; simulations: A.C.; mathematical modeling: S.C.N. and J.-L.D. ; results: A.C., S.C.N. and J.-L.D. ; writing: A.C. and S.C.N. All authors have read and agreed to the published version of the manuscript. This work was funded by the EU project CoCoRo, No. 270382, call FP7-ICT-2009-6, and the RoboCoenosis project, No. 899520, H2020-EU.1.2.1--FET Open program. Not applicable.