Formal Definitions of Unbounded Evolution and Innovation Reveal Universal Mechanisms for Open-Ended Evolution in Dynamical Systems

Open-ended evolution (OEE) is relevant to a variety of biological, artificial and technological systems, but has been challenging to reproduce in silico. Most theoretical efforts focus on key aspects of open-ended evolution as it appears in biology. We recast the problem as a more general one in dynamical systems theory, providing simple criteria for open-ended evolution based on two hallmark features: unbounded evolution and innovation. We define unbounded evolution as patterns that are non-repeating within the expected Poincare recurrence time of an equivalent isolated system, and innovation as trajectories not observed in isolated systems. As a case study, we implement novel variants of cellular automata (CA) in which the update rules are allowed to vary with time in three alternative ways. Each is capable of generating conditions for open-ended evolution, but vary in their ability to do so. We find that state-dependent dynamics, widely regarded as a hallmark of life, statistically out-performs other candidate mechanisms, and is the only mechanism to produce open-ended evolution in a scalable manner, essential to the notion of ongoing evolution. This analysis suggests a new framework for unifying mechanisms for generating OEE with features distinctive to life and its artifacts, with broad applicability to biological and artificial systems.Comment: Main document: 17 pages, Supplement: 21 pages Presented at OEE2: The Second Workshop on Open-Ended Evolution, 15th International Conference on the Synthesis and Simulation of Living Systems (ALIFE XV), Canc\'un, Mexico, 4-8 July 2016 (http://www.tim-taylor.com/oee2/

Integrated Information Theory and Isomorphic Feed-Forward Philosophical Zombies

Any theory amenable to scientific inquiry must have testable consequences. This minimal criterion is uniquely challenging for the study of consciousness, as we do not know if it is possible to confirm via observation from the outside whether or not a physical system knows what it feels like to have an inside - a challenge referred to as the "hard problem" of consciousness. To arrive at a theory of consciousness, the hard problem has motivated the development of phenomenological approaches that adopt assumptions of what properties consciousness has based on first-hand experience and, from these, derive the physical processes that give rise to these properties. A leading theory adopting this approach is Integrated Information Theory (IIT), which assumes our subjective experience is a "unified whole", subsequently yielding a requirement for physical feedback as a necessary condition for consciousness. Here, we develop a mathematical framework to assess the validity of this assumption by testing it in the context of isomorphic physical systems with and without feedback. The isomorphism allows us to isolate changes in $\Phi$ without affecting the size or functionality of the original system. Indeed, we show that the only mathematical difference between a "conscious" system with $\Phi>0$ and an isomorphic "philosophical zombies" with $\Phi=0$ is a permutation of the binary labels used to internally represent functional states. This implies $\Phi$ is sensitive to functionally arbitrary aspects of a particular labeling scheme, with no clear justification in terms of phenomenological differences. In light of this, we argue any quantitative theory of consciousness, including IIT, should be invariant under isomorphisms if it is to avoid the existence of isomorphic philosophical zombies and the epistemological problems they pose.Comment: 13 page

Health Disparities Among Racial and Ethnic Minority Firefighters

ABSTRACT Background: Racial/ethnic minorities are substantially underrepresented in the fire service and this situation is unique when compared to similarly mentally and physically demanding and hazardous occupations such as the military and law enforcement. There is little systematic research to provide greater clarity about this significant disparity. The purpose of this study is to examine physical and behavioral health issues of racial/ethnic minority firefighters when compared to their white, non-Hispanic counterparts and potentially identify areas for future research that might assist in improving their substantial underrepresentation. Materials and Methods: We report the results of a secondary analysis of data combining the baseline evaluations of two different firefighter health studies, the Firefighter Injury and Risk Evaluation (FIRE) and Fuel 2 Fight (F2F) studies. Male career firefighters (N=1,404) were from 31 fire departments across the US and its territories. White, non-Hispanic firefighters comprised 72.5% of the sample (n=1,018) and 27.5% classified themselves as a racial/ethnic minority. Firefighters who agreed to participate comprised 94% (F2F) and 97% (FIRE) of those available and all underwent assessments including body composition, fitness, and general/behavioral health, and job satisfaction. Results: We examined differences in health and job status between minority and non-minority firefighters and between firefighters in minority- (MDCs) and white-dominated communities (WDCs). After adjusting for potential confounds, there were significant main effects for the individual minority status vs. non-minority status on both BMI and BF%, indicating that minority firefighters had significantly higher average BMI (28.8±0.3kg/m2) and BF% (24.7± 0.7%) when compared to their white, non-Hispanic colleagues (27.7±0.2kg/m2and 23.1±0.6% for BMI and BF%, respectively). Minority firefighters also were 59% more likely to be obese (adjusted [A]OR=1.59; 95% CI=1.16-2.18). Firefighters serving in MDCs reported significantly more poor health days (Mean±SE; 3.2±0.2 days) than firefighters serving in WDCs (2.8±0.2 days; p=0.038). In addition, minority firefighters reported significantly more poor health days (3.6±0.4 days) than their non-minority colleagues (2.8±0.2 days; p=0.003), while the interaction indicates that minority firefighters in MDCs reported more poor health days than the other groups (p Conclusions: Individual and community minority status (i.e., ethnic density effect) were both significantly associated with a number of important health status indicators, with racial/ethnic minority firefighters demonstrating greater risk for unfavorable body composition and more poor physical health days. In addition, minority firefighters in WDCs reported the highest prevalence of lifetime diagnosis of depression by a physician, while minority firefighters in MDCs had the lowest. Many of these health status indicators have recently been studied within the context of experiences with discrimination, demonstrating that racial discrimination is associated with greater risk for obesity, depression, and poor physical and mental health and could be contributing to health disparities and potentially negatively impacting racial/ethnic minority firefighter health, safety, and retention

Clone Swarms: Learning to Predict and Control Multi-Robot Systems by Imitation

In this paper, we propose SwarmNet -- a neural network architecture that can learn to predict and imitate the behavior of an observed swarm of agents in a centralized manner. Tested on artificially generated swarm motion data, the network achieves high levels of prediction accuracy and imitation authenticity. We compare our model to previous approaches for modelling interaction systems and show how modifying components of other models gradually approaches the performance of ours. Finally, we also discuss an extension of SwarmNet that can deal with nondeterministic, noisy, and uncertain environments, as often found in robotics applications

Assembly Theory Explains and Quantifies the Emergence of Selection and Evolution

Since the time of Darwin, scientists have struggled to reconcile the evolution of biological forms in a universe determined by fixed laws. These laws underpin the origin of life, evolution, human culture and technology, as set by the boundary conditions of the universe, however these laws cannot predict the emergence of these things. By contrast evolutionary theory works in the opposite direction, indicating how selection can explain why some things exist and not others. To understand how open-ended forms can emerge in a forward-process from physics that does not include their design, a new approach to understand the non-biological to biological transition is necessary. Herein, we present a new theory, Assembly Theory (AT), which explains and quantifies the emergence of selection and evolution. In AT, the complexity of an individual observable object is measured by its Assembly Index (a), defined as the minimal number of steps needed to construct the object from basic building blocks. Combining a with the copy number defines a new quantity called Assembly which quantifies the amount of selection required to produce a given ensemble of objects. We investigate the internal structure and properties of assembly space and quantify the dynamics of undirected exploratory processes as compared to the directed processes that emerge from selection. The implementation of assembly theory allows the emergence of selection in physical systems to be quantified at any scale as the transition from undirected-discovery dynamics to a selected process within the assembly space. This yields a mechanism for the onset of selection and evolution and a formal approach to defining life. Because the assembly of an object is easily calculable and measurable it is possible to quantify a lower limit on the amount of selection and memory required to produce complexity uniquely linked to biology in the universe.Comment: 22 pages, 7 figure