Emerging robot swarm traffic

We discuss traffic patterns generated by swarms of robots while commuting to and from a base station. The overall question is whether to explicitly organise the traffic or whether a certain regularity develops `naturally'. Human driven motorized traffic is rigidly structured in two lanes. However, army ants develop a three-lane pattern in their traffic, while human pedestrians generate a main trail and secondary trials in either direction. Our robot swarm approach is bottom-up: designing individual agents we first investigate the mathematics of cases occurring when applying the artificial potential field method to three 'perfect' robots. We show that traffic lane pattern will not be disturbed by the internal system of forces. Next, we define models of sensor designs to account for the practical fact that robots (and ants) have limited visibility and compare the sensor models in groups of three robots. In the final step we define layouts of a highway: an unbounded open space, a trail with surpassable edges and a hard defined (walled) highway. Having defined the preliminaries we run swarm simulations and look for emerging traffic patterns. Apparently, depending on the initial situation a variety of lane patterns occurs, however, high traffic densities do delay the emergence of traffic lanes considerably. Overall we conclude that regularities do emerge naturally and can be turned into an advantage to obtain efficient robot traffic

Academic team formation as evolving hypergraphs

This paper quantitatively explores the social and socio-semantic patterns of constitution of academic collaboration teams. To this end, we broadly underline two critical features of social networks of knowledge-based collaboration: first, they essentially consist of group-level interactions which call for team-centered approaches. Formally, this induces the use of hypergraphs and n-adic interactions, rather than traditional dyadic frameworks of interaction such as graphs, binding only pairs of agents. Second, we advocate the joint consideration of structural and semantic features, as collaborations are allegedly constrained by both of them. Considering these provisions, we propose a framework which principally enables us to empirically test a series of hypotheses related to academic team formation patterns. In particular, we exhibit and characterize the influence of an implicit group structure driving recurrent team formation processes. On the whole, innovative production does not appear to be correlated with more original teams, while a polarization appears between groups composed of experts only or non-experts only, altogether corresponding to collectives with a high rate of repeated interactions

Euro Zone Crisis Management and the New Social Europe

This article analyzes the changes in European governance since the beginning of the euro crisis in relation to the project of constructing Social Europe. The article tracks the incorporation of a structural reform agenda originally designed as bailout conditionality for countries on the verge of default into EU economic governance as a strategy for growth. Beyond the contestable grounds of this reform agenda, its adoption by the EU in the mode of crisis management poses serious questions of legitimacy. The new enhanced economic coordination process includes obligatory guidelines in domains under the legislative competence of Member States, such as labor regulation and taxation, under the guise of a technocratic imperative. The article also shows that despite the intensely neoliberal character of the proposed structural reforms, the Commission has foregrounded the protection of Europe’s welfare regimes as a key reason for reform. In reality, such reforms would dramatically alter welfare regimes, emptying out traditional welfarist goals such as the decommodification of labor without appropriate political processes. This article argues that these developments are likely to challenge the already weakened legitimacy of the European Union

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

MGA trajectory planning with an ACO-inspired algorithm

Given a set of celestial bodies, the problem of finding an optimal sequence of gravity assist manoeuvres, deep space manoeuvres (DSM) and transfer arcs connecting two or more bodies in the set is combinatorial in nature. The number of possible paths grows exponentially with the number of celestial bodies. Therefore, the design of an optimal multiple gravity assist (MGA) trajectory is a NP-hard mixed combinatorial-continuous problem, and its automated solution would greatly improve the assessment of multiple alternative mission options in a shorter time. This work proposes to formulate the complete automated design of a multiple gravity assist trajectory as an autonomous planning and scheduling problem. The resulting scheduled plan will provide the planetary sequence for a multiple gravity assist trajectory and a good estimation of the optimality of the associated trajectories. We propose the use of a two-dimensional trajectory model in which pairs of celestial bodies are connected by transfer arcs containing one DSM. The problem of matching the position of the planet at the time of arrival is solved by varying the pericentre of the preceding swing-by, or the magnitude of the launch excess velocity, for the first arc. By using this model, for each departure date we can generate a full tree of possible transfers from departure to destination. Each leaf of the tree represents a planetary encounter and a possible way to reach that planet. An algorithm inspired by Ant Colony Optimization (ACO) is devised to explore the space of possible plans. The ants explore the tree from departure to destination adding one node at the time: every time an ant is at a node, a probability function is used to select one of the remaining feasible directions. This approach to automatic trajectory planning is applied to the design of optimal transfers to Saturn and among the Galilean moons of Jupiter, and solutions are compared to those found through traditional genetic-algorithm-based techniques

Anthropocene, Capitalocene, Machinocene: Illusions of instrumental reason

In their seminal work, Dialectics of Enlightenment, Horkheimer and Adorno interpreted capitalism as the irrational monetization of nature. In the present work, I analyze three 21st century concepts, Anthropocene, Capitalocene and Machinocene, in light of Horkheimer and Adorno’s arguments and recent arguments from the philosophy of biology. The analysis reveals a remarkable prescience of the term “instrumental reason”, which is present in each of the three concepts in a profound and cryptic way. In my interpretation, the term describes the propensity of science based on the notion of physicalism to interpret nature as the machine analyzable and programmable by the human reason. As a result, the Anthropocene concept is built around the mechanicist model, which may be presented as the metaphor of the car without brakes. In a similar fashion, the Machinocene concept predicts the emergence of the mechanical mind, which will dominate nature in the near future. Finally, the Capitalocene concept turns a perfectly rational ambition to expand knowledge into an irrational obsession with over-knowledge, by employing the institutionalized science as the engine of capitalism without brakes. The common denominator of all three concepts is the irrational propensity to legitimize self-destruction. Potential avenues for countering the effects of “instrumental reason” are suggested