Evolving Collective Driving Behaviors

Recently there has been increased research interest in developing autonomous, adaptive control systems of self-driving vehicles. However, there has been little work on synthesizing collective behaviours for autonomous vehicles that must safely interact and coordinate so as traffic throughput on any given road network is maximized. This work uses neuro-evolution to automate car controller design, testing various vehicle sensor configurations and collective driving behaviours resulting from car interactions on roads without constraints of traffic lights, stop signals at intersections or lanes that vehicles must adhere to and thus simulates potential future scenarios where vehicles must drive autonomously without special road infrastructure constraints. Results indicate that neuro-evolution is an effective method for automatically synthesizing collective driving behaviours that are behaviourally robust across a range of vehicle sensor configurations and generalize to different task environments

Autonomous Intersection Driving with Neuro-Evolution

Neuro-Evolution (NE) has been used to evolve controllers in land-based vehicles that accomplish various tasks. However, there has been little work on evolving coordinated movement for maximizing traffic flow through intersections. This study used NE to synthesize collective driving behaviors for given road networks (interconnected intersections), where there were no traffic signals to assist with vehicle coordination and navigation. Rather, NE automates controller design where collective driving behavior emerges in response to the task of maximizing traffic throughput and minimizing delays at intersections

Robust and fragile Werner states in the collective dephasing

We investigate the concurrence and Bell violation of the standard Werner state or Werner-like states in the presence of collective dephasing. It is shown that the standard Werner state and certain kinds of Werner-like states are robust against the collective dephasing, and some kinds of Werner-like states is fragile and becomes completely disentangled in a finite-time. The threshold time of complete disentanglement of the fragile Werner-like states is given. The influence of external driving field on the finite-time disentanglement of the standard Werner state or Werner-like states is discussed. Furthermore, we present a simple method to control the stationary state entanglement and Bell violation of two qubits. Finally, we show that the theoretical calculations of fidelity based on the initial Werner state assumption well agree with previous experimental results.Comment: 7 pages, 6 figures, 1 table, RevTex4, Accepted by EPJ

Evolving collective behavior in an artificial ecology

Collective behavior refers to coordinated group motion, common to many animals. The dynamics of a group can be seen as a distributed model, each “animal” applying the same rule set. This study investigates the use of evolved sensory controllers to produce schooling behavior. A set of artificial creatures “live” in an artificial world with hazards and food. Each creature has a simple artificial neural network brain that controls movement in different situations. A chromosome encodes the network structure and weights, which may be combined using artificial evolution with another chromosome, if a creature should choose to mate. Prey and predators coevolve without an explicit fitness function for schooling to produce sophisticated, nondeterministic, behavior. The work highlights the role of species’ physiology in understanding behavior and the role of the environment in encouraging the development of sensory systems

Human Computation and Convergence

Humans are the most effective integrators and producers of information, directly and through the use of information-processing inventions. As these inventions become increasingly sophisticated, the substantive role of humans in processing information will tend toward capabilities that derive from our most complex cognitive processes, e.g., abstraction, creativity, and applied world knowledge. Through the advancement of human computation - methods that leverage the respective strengths of humans and machines in distributed information-processing systems - formerly discrete processes will combine synergistically into increasingly integrated and complex information processing systems. These new, collective systems will exhibit an unprecedented degree of predictive accuracy in modeling physical and techno-social processes, and may ultimately coalesce into a single unified predictive organism, with the capacity to address societies most wicked problems and achieve planetary homeostasis.Comment: Pre-publication draft of chapter. 24 pages, 3 figures; added references to page 1 and 3, and corrected typ

On Self-Organized Criticality and Synchronization in Lattice Models of Coupled Dynamical Systems

Lattice models of coupled dynamical systems lead to a variety of complex behaviors. Between the individual motion of independent units and the collective behavior of members of a population evolving synchronously, there exist more complicated attractors. In some cases, these states are identified with self-organized critical phenomena. In other situations, with clusterization or phase-locking. The conditions leading to such different behaviors in models of integrate-and-fire oscillators and stick-slip processes are reviewed.Comment: 41 pages. Plain LaTeX. Style included in main file. To appear as an invited review in Int. J. Modern Physics B. Needs eps

The Ambivalent Role of Mimetic Behaviors in Proximity Dynamics: Evidences on the French “Silicon Sentier”

This articles examines the peculiar role of mimetic behaviors in co-location processes. We start showing that geographical proximity between agents and/or firms is not a sufficient nor necessary condition for the collective performance of clusters. Other types of socio-economic proximities characterize clusters, and our purpose is to show that, among the several ways to analyze the complex links between proximities and clusters, the theoretical outlook on the role played by mimetic interactions in co-location processes are certainly one of the most promising. Mimetic behaviors of location (in economics and sociology) are introduced in order to demonstrate that co-location processes can be the result of sequentiality, uncertainty, legitimacy and non market interactions, rather than full rational and isolated decisions and pure strategic market interactions. According to the type of mimetic behavior at work in the clustering process, the nature of socio-economic proximity can differ and have a strong influence of the “evolutionary stability” of clusters. All these theoretical considerations are illustrated through the emblematic French case of “Silicon Sentier”, cluster which has gathered together three hundred firms of the French net-economy (the famous “dotcom”) during the Internet bubble swelling.cluster, mimetic interactions, proximity, stability, Silicon Sentier