We present a dynamical systems analysis of a decision-making mechanism inspired by collective choice in house-hunting honeybee swarms, revealing the crucial role of cross-inhibitory 'stop-signalling' ...in improving the decision-making capabilities. We show that strength of cross-inhibition is a decision-parameter influencing how decisions depend both on the difference in value and on the mean value of the alternatives; this is in contrast to many previous mechanistic models of decision-making, which are typically sensitive to decision accuracy rather than the value of the option chosen. The strength of cross-inhibition determines when deadlock over similarly valued alternatives is maintained or broken, as a function of the mean value; thus, changes in cross-inhibition strength allow adaptive time-dependent decision-making strategies. Cross-inhibition also tunes the minimum difference between alternatives required for reliable discrimination, in a manner similar to Weber's law of just-noticeable difference. Finally, cross-inhibition tunes the speed-accuracy trade-off realised when differences in the values of the alternatives are sufficiently large to matter. We propose that the model, and the significant role of the values of the alternatives, may describe other decision-making systems, including intracellular regulatory circuits, and simple neural circuits, and may provide guidance in the design of decision-making algorithms for artificial systems, particularly those functioning without centralised control.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The evolution of leadership in migratory populations depends not only on costs and benefits of leadership investments but also on the opportunities for individuals to rely on cues from others through ...social interactions. We derive an analytically tractable adaptive dynamic network model of collective migration with fast timescale migration dynamics and slow timescale adaptive dynamics of individual leadership investment and social interaction. For large populations, our analysis of bifurcations with respect to investment cost explains the observed hysteretic effect associated with recovery of migration in fragmented environments. Further, we show a minimum connectivity threshold above which there is evolutionary branching into leader and follower populations. For small populations, we show how the topology of the underlying social interaction network influences the emergence and location of leaders in the adaptive system. Our model and analysis can be extended to study the dynamics of collective tracking or collective learning more generally. Thus, this work may inform the design of robotic networks where agents use decentralized strategies that balance direct environmental measurements with agent interactions.
•Analytically tractable, two-timescale, network-dependent collective migration model.•Bifurcations explain hysteresis in migration recovery in fragmented environments.•Minimum connectivity for evolutionary branching into leaders and followers.•Social interaction graph influences emergence and location of leaders.
The replicator-mutator equations from evolutionary dynamics serve as a model for the evolution of language, behavioral dynamics in social networks, and decision-making dynamics in networked ...multiagent systems. Analysis of the stable equilibria of these dynamics has been a focus in the literature, where symmetry in fitness functions is typically assumed. We explore asymmetry in fitness and show that the replicator-mutator equations exhibit Hopf bifurcations and limit cycles. We prove conditions for the existence of stable limit cycles arising from multiple distinct Hopf bifurcations of the dynamics in the case of circulant fitness matrices. In the noncirculant case we illustrate how stable limit cycles of the dynamics are coupled to embedded directed cycles in the payoff graph. The limit cycles correspond to oscillations of grammar dominance in language evolution and to oscillations in behavioral preferences in social networks; for decision-making systems, the limit cycles correspond to sustained oscillations in decisions across the group. PUBLICATION ABSTRACT
The study of collective behavior involves the analysis of interactions among a set of agents that yield collective outcomes at the level of the group. The behavior is said to be emergent when it ...cannot be understood simply as the sum of its constituent parts. Further, group-level outcomes can in turn influence individual interactions. The complexity of this interplay makes the study of emergence challenging and exciting. This dissertation is focused on the study of emergent collective behavior from the perspective of evolution. Evolution is a simple yet powerful algorithm, which when acting on interacting entities in a dynamic environment, yields an array of fascinating behavior as manifest in the natural world. Natural collectives display a wide variety of cooperative behavior and have evolved to efficiently manage the inherent tradeoff between robust behavior and adaptability to dynamic environments. These properties have motivated the design of bio-inspired algorithms for sensing and decision-making in robotic collectives. In this work, we study the evolutionary mechanisms for cooperation and tradeoff management in biological collectives, with a focus on four related topics: replicator-mutator dynamics, collective migration, collective pursuit and evasion, and decision-making dynamics in swarms. The replicator-mutator dynamics define a canonical model from evolutionary theory and have recently been used to study the evolution of language and the behavioral dynamics of social networks. While the analysis of stable equilibria of these dynamics has been a focus in the literature, we prove that certain conditions suffice for the equations to exhibit stable limit cycles. These cycles correspond to oscillations of grammar dominance in language evolution and to oscillations in behavioral preferences in social networks. For the collective migration problem, it is well-established that a small group of leaders can guide a large swarm of followers. It is less clear how presumably self-interested individuals have evolved to take on such divergent roles. We design a network-based evolutionary model to understand the evolution of leadership in migration, with a focus on the role of network topology on the emergent dynamics. Pursuit and evasive behaviors are ubiquitous in biology and are key drivers for collective motion. We use computational simulations and analytical calculations to study a co-evolving pursuit and evasive system, and incorporate the evolved strategies in a cyclic pursuit-evasion collective motion model. The 'stop-signaling' inhibitory mechanism has been recently shown to be critical to the decentralized decision-making dynamics in honeybee swarms. We investigate bifurcations in a model of swarm decision-making as a function of the stop-signal and the values of different alternatives, and present a comprehensive analysis of the dynamics of the model.
The goal of this work is to stabilize the shape and orientation of formations of N identical and fully actuated agents, each governed by double-integrator dynamics. Using stability and rigidity ...properties inherent to tensegrity structures, we first design a tensegrity-based, globally exponentially stable control law in one dimension. This stabilizes given inter-agent spacing along the line, thereby enabling shape control of one-dimensional formations. We then couple one-dimensional control laws along independent orthogonal axes to design a distributed control law capable of stabilizing arbitrary shapes and orientations in n dimensions. We also present two methods for formation shape and orientation change, one using smooth parameter variations of the control law, and the other, an n-step collision-free algorithm for shape change between any two formations in n-dimensional space.
The replicator-mutator equations from evolutionary dynamics serve as a model for the evolution of language, behavioral dynamics in social networks, and decision-making dynamics in networked ...multi-agent systems. Analysis of the stable equilibria of these dynamics has been a focus in the literature, where symmetry in fitness functions is typically assumed. We explore asymmetry in fitness and show that the replicator-mutator equations exhibit Hopf bifurcations and limit cycles. We prove conditions for the existence of stable limit cycles for the dynamics in the case of circulant fitness matrices, and illustrate their existence in the noncirculant case. For decision-making networks, these limit cycles correspond to sustained oscillations in decisions across the group.
The evolution of leadership in migratory populations depends not only on costs and benefits of leadership investments but also on the opportunities for individuals to rely on cues from others through ...social interactions. We derive an analytically tractable adaptive dynamic network model of collective migration with fast timescale migration dynamics and slow timescale adaptive dynamics of individual leadership investment and social interaction. For large populations, our analysis of bifurcations with respect to investment cost explains the observed hysteretic effect associated with recovery of migration in fragmented environments. Further, we show a minimum connectivity threshold above which there is evolutionary branching into leader and follower populations. For small populations, we show how the topology of the underlying social interaction network influences the emergence and location of leaders in the adaptive system. Our model and analysis can describe other adaptive network dynamics involving collective tracking or collective learning of a noisy, unknown signal, and likewise can inform the design of robotic networks where agents use decentralized strategies that balance direct environmental measurements with agent interactions.
The ability to predict the mechanical properties of organic semiconductors is of critical importance for roll-to-roll production and thermomechanical reliability of organic electronic devices. Here, ...we describe the use of coarse-grained molecular dynamics simulations to predict the density, tensile modulus, Poisson ratio, and glass transition temperature for poly(3-hexylthiophene) (P3HT) and its blend with C60. In particular, we show that the resolution of the coarse-grained model has a strong effect on the predicted properties. We find that a one-site model, in which each 3-hexylthiophene unit is represented by one coarse-grained bead, predicts significantly inaccurate values of density and tensile modulus. In contrast, a three-site model, with one coarse-grained bead for the thiophene ring and two for the hexyl chain, predicts values that are very close to experimental measurements (density = 0.955 g cm–3, tensile modulus = 1.23 GPa, Poisson ratio = 0.35, and glass transition temperature = 290 K). The model also correctly predicts the strain-induced alignment of chains as well as the vitrification of P3HT by C60 and the corresponding increase in the tensile modulus (tensile modulus = 1.92 GPa, glass transition temperature = 310 K). We also observe a decrease in the radius of gyration and the density of entanglements of the P3HT chains with the addition C60 which may contribute to the experimentally noted brittleness of the composite material. Although extension of the model to poly(3-alkylthiophenes) (P3ATs) containing side chains longer than hexyl groupsnonyl (N) and dodecyl (DD) groupscorrectly predicts the trend of decreasing modulus with increasing length of the side chain measured experimentally, obtaining absolute agreement for P3NT and P3DDT could not be accomplished by a straightforward extension of the three-site coarse-grained model, indicating limited transferability of such models. Nevertheless, the accurate values obtained for P3HT and P3HT:C60 blends suggest that coarse graining is a valuable approach for predicting the thermomechanical properties of organic semiconductors of similar or more complex architectures.
Nephrotic syndrome represents a condition in pediatric nephrology typified by a relapsing and remitting course, proteinuria and the presence of edema. The PROMIS measures have previously been studied ...and validated in cross-sectional studies of children with nephrotic syndrome. This study was designed to longitudinally validate the PROMIS measures in pediatric nephrotic syndrome.
One hundred twenty seven children with nephrotic syndrome between the ages of 8 and 17 years participated in this prospective cohort study. Patients completed a baseline assessment while their nephrotic syndrome was active, a follow-up assessment at the time of their first complete proteinuria remission or study month 3 if no remission occurred, and a final assessment at study month 12. Participants completed six PROMIS measures (Mobility, Fatigue, Pain Interference, Depressive Symptoms, Anxiety, and Peer Relationships), the PedsQL version 4.0, and two global assessment of change items.
Disease status was classified at each assessment: nephrotic syndrome active in 100% at baseline, 33% at month 3, and 46% at month 12. The PROMIS domains of Mobility, Fatigue, Pain Interference, Depressive Symptoms, and Anxiety each showed a significant overall improvement over time (p < 0.001). When the PROMIS measures were compared to the patients' global assessment of change, the domains of Mobility, Fatigue, Pain Interference, and Anxiety consistently changed in an expected fashion. With the exception of Pain Interference, change in PROMIS domain scores did not correlate with changes in disease activity. PROMIS domain scores were moderately correlated with analogous PedsQL domain scores.
This study demonstrates that the PROMIS Mobility, Fatigue, Pain Interference, and Anxiety domains are sensitive to self-reported changes in disease and overall health status over time in children with nephrotic syndrome. The lack of significant anchoring to clinically defined nephrotic syndrome disease active and remission status may highlight an opportunity to improve the measurement of HRQOL in children with nephrotic syndrome through the development of a nephrotic syndrome disease-specific HRQOL measure.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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