Ant routing algorithm for the Lightning Network

We propose a decentralized routing algorithm that can be implemented in Bitcoin Lightning Network. All nodes in the network contribute equally to path searching. The algorithm is inspired from ant path searching algorithms.Comment: 10 pages, 1 figur

Social Evolution: New Horizons

Cooperation is a widespread natural phenomenon yet current evolutionary thinking is dominated by the paradigm of selfish competition. Recent advanced in many fronts of Biology and Non-linear Physics are helping to bring cooperation to its proper place. In this contribution, the most important controversies and open research avenues in the field of social evolution are reviewed. It is argued that a novel theory of social evolution must integrate the concepts of the science of Complex Systems with those of the Darwinian tradition. Current gene-centric approaches should be reviewed and com- plemented with evidence from multilevel phenomena (group selection), the constrains given by the non-linear nature of biological dynamical systems and the emergent nature of dissipative phenomena.Comment: 16 pages 5 figures, chapter in forthcoming open access book "Frontiers in Ecology, Evolution and Complexity" CopIt-arXives 2014, Mexic

Ant-Inspired Density Estimation via Random Walks

Many ant species employ distributed population density estimation in applications ranging from quorum sensing [Pra05], to task allocation [Gor99], to appraisal of enemy colony strength [Ada90]. It has been shown that ants estimate density by tracking encounter rates -- the higher the population density, the more often the ants bump into each other [Pra05,GPT93]. We study distributed density estimation from a theoretical perspective. We prove that a group of anonymous agents randomly walking on a grid are able to estimate their density within a small multiplicative error in few steps by measuring their rates of encounter with other agents. Despite dependencies inherent in the fact that nearby agents may collide repeatedly (and, worse, cannot recognize when this happens), our bound nearly matches what would be required to estimate density by independently sampling grid locations. From a biological perspective, our work helps shed light on how ants and other social insects can obtain relatively accurate density estimates via encounter rates. From a technical perspective, our analysis provides new tools for understanding complex dependencies in the collision probabilities of multiple random walks. We bound the strength of these dependencies using $local\ mixing\ properties$ of the underlying graph. Our results extend beyond the grid to more general graphs and we discuss applications to size estimation for social networks and density estimation for robot swarms

The effect of sex-allocation biasing on the evolution of worker policing in hymenopteran societies

Mutual policing is thought to be important in conflict suppression at all levels of biological organization. In hymenopteran societies (bees, ants, and wasps), multiple mating by queens favors mutual policing of male production among workers (worker policing). However, worker policing of male production is proving to be more widespread than predicted by relatedness patterns, occurring in societies headed by single-mated queens in which, paradoxically, workers are more related to the workers' sons that they kill than the queen's sons that they spare. Here we develop an inclusive-fitness model to show that a second reproductive conflict, the conflict over sex allocation, can explain the evolution of worker policing contrary to relatedness predictions. Among ants, and probably other social Hymenoptera, workers kill males to favor their more related sisters. Importantly, males are killed at the larval stage, presumably because workers cannot determine the sex of queen-laid eggs. Sex-allocation biasing favors worker policing because policing removes some males (the workers' sons) at low cost at the egg stage rather than at higher cost at the larval stage. Our model reveals an important interaction between two reproductive conflicts in which the presence of one conflict (sex allocation) favors the suppression of the other (male production by workers)

The effect of sex-allocation biasing on the evolution of worker policing in hymenopteran societies

Mutual policing is thought to be important in conflict suppression at all levels of biological organization. In hymenopteran societies (bees, ants, and wasps), multiple mating by queens favors mutual policing of male production among workers (worker policing). However, worker policing of male production is proving to be more widespread than predicted by relatedness patterns, occurring in societies headed by single-mated queens in which, paradoxically, workers are more related to the workers' sons that they kill than the queen's sons that they spare. Here we develop an inclusive-fitness model to show that a second reproductive conflict, the conflict over sex allocation, can explain the evolution of worker policing contrary to relatedness predictions. Among ants, and probably other social Hymenoptera, workers kill males to favor their more related sisters. Importantly, males are killed at the larval stage, presumably because workers cannot determine the sex of queen-laid eggs. Sex-allocation biasing favors worker policing because policing removes some males (the workers' sons) at low cost at the egg stage rather than at higher cost at the larval stage. Our model reveals an important interaction between two reproductive conflicts in which the presence of one conflict (sex allocation) favors the suppression of the other (male production by workers)

Substrate Temperature Constrains Recruitment and Trail Following Behavior in Ants

In many ant species, foragers use pheromones to communicate the location of resources to nestmates. Mass-recruiting species deposit long-lasting anonymous chemical trails, while group-recruiting species use temporary chemical trails. We studied how high temperature influenced the foraging behavior of a mass-recruiting species (Tapinoma nigerrimum) and a group-recruiting species (Aphaenogaster senilis) through pheromone decay. First, under controlled laboratory conditions, we examined the effect of temperature on the trail pheromone of both species. A substrate, simulating soil, marked with gaster extract was heated for 10 min. at 25°, 35°, 45°, or 55 °C and offered to workers in a choice test. Heating gaster extract reduced the trail following behavior of the mass-recruiters significantly more than that of the group-recruiters. Second, analyses of the chemicals present on the substrate indicated that most T. nigerrimum gaster secretions vanished at 25 °C, and only iridodials persisted up to 55 °C. By contrast, A. senilis secretions were less volatile and resisted better to elevated temperatures to some extent. However, at 55 °C, the only chemicals that persisted were nonadecene and nonadecane. Overall, our results suggest that the foraging behavior of the group-recruiting species A. senilis is less affected by pheromone evaporation than that of the mass-recruiting species T. nigerrimum. This group-recruiting species might, thus, be particularly adapted to environments with fluctuating temperatures. © 2012 Springer Science+Business Media, LLC.Peer Reviewe

Collaborative search on the plane without communication

We generalize the classical cow-path problem [7, 14, 38, 39] into a question that is relevant for collective foraging in animal groups. Specifically, we consider a setting in which k identical (probabilistic) agents, initially placed at some central location, collectively search for a treasure in the two-dimensional plane. The treasure is placed at a target location by an adversary and the goal is to find it as fast as possible as a function of both k and D, where D is the distance between the central location and the target. This is biologically motivated by cooperative, central place foraging such as performed by ants around their nest. In this type of search there is a strong preference to locate nearby food sources before those that are further away. Our focus is on trying to find what can be achieved if communication is limited or altogether absent. Indeed, to avoid overlaps agents must be highly dispersed making communication difficult. Furthermore, if agents do not commence the search in synchrony then even initial communication is problematic. This holds, in particular, with respect to the question of whether the agents can communicate and conclude their total number, k. It turns out that the knowledge of k by the individual agents is crucial for performance. Indeed, it is a straightforward observation that the time required for finding the treasure is $\Omega$(D + D 2 /k), and we show in this paper that this bound can be matched if the agents have knowledge of k up to some constant approximation. We present an almost tight bound for the competitive penalty that must be paid, in the running time, if agents have no information about k. Specifically, on the negative side, we show that in such a case, there is no algorithm whose competitiveness is O(log k). On the other hand, we show that for every constant \epsilon \textgreater{} 0, there exists a rather simple uniform search algorithm which is $O( \log^{1+\epsilon} k)$-competitive. In addition, we give a lower bound for the setting in which agents are given some estimation of k. As a special case, this lower bound implies that for any constant \epsilon \textgreater{} 0, if each agent is given a (one-sided) $k^\epsilon$-approximation to k, then the competitiveness is $\Omega$(log k). Informally, our results imply that the agents can potentially perform well without any knowledge of their total number k, however, to further improve, they must be given a relatively good approximation of k. Finally, we propose a uniform algorithm that is both efficient and extremely simple suggesting its relevance for actual biological scenarios