Adapting Swarm Intelligence for the Self-Assembly of Prespecified Artificial Structures

The self-assembly problem involves designing individual behaviors that a collection of agents can follow in order to form a given target structure. An effective solution would potentially allow self-assembly to be used as an automated construction tool, for example, in dangerous or inaccessible environments. However, existing methodologies are generally limited in that they are either only capable of assembling a very limited range of simple structures, or only applicable in an idealized environment having few or no constraints on the agents' motion. The research presented here seeks to overcome these limitations by studying the self-assembly of a diverse class of non-trivial structures (building, bridge, etc.) from different-sized blocks, whose motion in a continuous, three-dimensional environment is constrained by gravity and block impenetrability. These constraints impose ordering restrictions on the self-assembly process, and necessitate the assembly and disassembly of temporary structures such as staircases. It is shown that self-assembly under these conditions can be accomplished through an integration of several techniques from the field of swarm intelligence. Specifically, this work extends and incorporates computational models of distributed construction, collective motion, and communication via local signaling. These mechanisms enable blocks to determine where to deposit themselves, to effectively move through continuous space, and to coordinate their behavior over time, while using only local information. Further, an algorithm is presented that, given a target structure, automatically generates distributed control rules that encode individual block behaviors. It is formally proved that under reasonable assumptions, these rules will lead to the emergence of correct system-level coordination that allows self-assembly to complete in spite of environmental constraints. The methodology is also verified experimentally by generating rules for a diverse set of structures, and testing them via simulations. Finally, it is shown that for some structures, the generated rules are able to parsimoniously capture the necessary behaviors. This work yields a better understanding of the complex relationship between local behaviors and global structures in non-trivial self-assembly processes, and presents a step towards their use in the real world

Intersectionality as a Regulative Ideal

Appeals to intersectionality serve to remind us that social categories like race and gender cannot be adequately understood independently from each other. But what, exactly, is the intersectional thesis a thesis about? Answers to this question are remarkably diverse. Intersectionality is variously understood as a claim about the nature of social kinds, oppression, or experience ; about the limits of antidiscrimination law or identity politics ; or about the importance of fuzzy sets, multifactor analysis, or causal modeling in social science

Bottom-up construction of ontologies

Presents a particular way of building ontologies that proceeds in a bottom-up fashion. Concepts are defined in a way that mirrors the way their instances are composed out of smaller objects. The smaller objects themselves may also be modeled as being composed. Bottom-up ontologies are flexible through the use of implicit and, hence, parsimonious part-whole and subconcept-superconcept relations. The bottom-up method complements current practice, where, as a rule, ontologies are built top-down. The design method is illustrated by an example involving ontologies of pure substances at several levels of detail. It is not claimed that bottom-up construction is a generally valid recipe; indeed, such recipes are deemed uninformative or impossible. Rather, the approach is intended to enrich the ontology developer's toolki

Adapting Swarm Intelligence For The Self-Assembly And Optimization Of Networks

While self-assembly is a fairly active area of research in swarm intelligence and robotics, relatively little attention has been paid to the issues surrounding the construction of network structures. Here, methods developed previously for modeling and controlling the collective movements of groups of agents are extended to serve as the basis for self-assembly or "growth" of networks, using neural networks as a concrete application to evaluate this novel approach. One of the central innovations incorporated into the model presented here is having network connections arise as persistent "trails" left behind moving agents, trails that are reminiscent of pheromone deposits made by agents in ant colony optimization models. The resulting network connections are thus essentially a record of agent movements. The model's effectiveness is demonstrated by using it to produce two large networks that support subsequent learning of topographic and feature maps. Improvements produced by the incorporation of collective movements are also examined through computational experiments. These results indicate that methods for directing collective movements can be extended to support and facilitate network self-assembly. Additionally, the traditional self-assembly problem is extended to include the generation of network structures based on optimality criteria, rather than on target structures that are specified a priori. It is demonstrated that endowing the network components involved in the self-assembly process with the ability to engage in collective movements can be an effective means of generating computationally optimal network structures. This is confirmed on a number of challenging test problems from the domains of trajectory generation, time-series forecasting, and control. Further, this extension of the model is used to illuminate an important relationship between particle swarm optimization, which usually occurs in high dimensional abstract spaces, and self-assembly, which is normally grounded in real and simulated 2D and 3D physical spaces

Inference of single-cell phylogenies from lineage tracing data using Cassiopeia.

The pairing of CRISPR/Cas9-based gene editing with massively parallel single-cell readouts now enables large-scale lineage tracing. However, the rapid growth in complexity of data from these assays has outpaced our ability to accurately infer phylogenetic relationships. First, we introduce Cassiopeia-a suite of scalable maximum parsimony approaches for tree reconstruction. Second, we provide a simulation framework for evaluating algorithms and exploring lineage tracer design principles. Finally, we generate the most complex experimental lineage tracing dataset to date, 34,557 human cells continuously traced over 15 generations, and use it for benchmarking phylogenetic inference approaches. We show that Cassiopeia outperforms traditional methods by several metrics and under a wide variety of parameter regimes, and provide insight into the principles for the design of improved Cas9-enabled recorders. Together, these should broadly enable large-scale mammalian lineage tracing efforts. Cassiopeia and its benchmarking resources are publicly available at www.github.com/YosefLab/Cassiopeia

The foundations of a nation : framing Pakistan from 1940-1971 through international relations theory and postcolonialism

This paper explores the emerging integration of international relations theory with postcolonial scholarship and uses Pakistan’s state formation and history as a case study. It is argued that international relations theory privileges European experiences and history, which results in inaccurate assumptions about the outcomes of colonialism and origins of postcolonial independence. Pakistan’s unique development as a state founded on ideology and build out of an imperial/colonial system offers an opportunity for destabilizing Eurocentrism in international studies. Rather than favoring a singular outcome or conclusion, this paper demonstrates the plurality necessary for an inclusive historical analysis of state-power.Asian StudiesGlobal Policy Studie

Co-evolution in Manufacturing Systems Inspired by Biological Analogy

The artificial world experiences continuous changes that result in the evolution of design features of products and the capabilities of the corresponding manufacturing systems similar to the changes of species in the natural world. The idea of simulating the artificial world, based on the analogy between the symbiotic behaviour of products and manufacturing systems and the biological co-evolution of different species in nature, is expressed by a model and novel hypotheses regarding manufacturing co-evolution mechanism, preserving that co-evolution and using it for future planning and prediction. Biological analogy is also employed to drive the mathematical formulation of the model and its algorithms. Cladistics, a biological classification tool, is adapted and used to realize evolution trends of products and systems and their symbiosis was illustrated using another biological tool, tree reconciliation. A new mathematical method was developed to realize the co-development relationships between product features and manufacturing capabilities. It has been used for synthesizing / predicting new species of systems and products. The developed model was validated using machining and assembly case studies. Results have proven the proposed hypotheses, demonstrated the presence of manufacturing symbiosis and made predictions and synthesized new systems and products. The model has been also adapted for use in different applications such as; system layout design, identifying sustainable design features and products family redesign to promote modularity. The co-evolution model is significant as it closes the loop connecting products and systems to learn from their shared past development and predict their intertwined future, unlike available unidirectional design strategies. The economic life of manufacturing systems can be extended by better utilizing their available capabilities, since the co-evolution model directs products - systems development towards reaching a perfect co-evolution state. This research presents original ideas expressed by innovative co-evolution hypotheses in manufacturing, new mathematical model and algorithms, and demonstrates its advantages and benefits in a wide range of applications

Evaluation for an Open Society: Then and Now

Background: Karl Popper’s views about science and political economy remain relevant to evaluation theory and practice. His Open Society opus inspired pioneering contributions to experimental evaluation and shaped the evaluation discipline. Yet, his ideas are not widely known without the evaluation community even though populist leaders are once again threatening to undermine democracy.   Purpose: To define the Open Society, probe its epistemological tenets, confirm that they remain valid as the foundation of evaluation practice, identify the ways in which the operating environment for evaluation has changed and, against this background, propose a policy change agenda relevant to the contemporary evaluation discipline.   Setting: The Open Society is once again being undermined. Modern authoritarianism is tightening its grip. The lure of the strong man is once again gaining traction. The dominance of an international order grounded in democracy, human rights, and the rule of law is giving way to a world in which leaders are pursuing narrow nationalist and vested interests. In this troubled context, policy making has become more complex than when evaluation emerged out of the ashes of World War II. Economic and social dysfunctions have led to extraordinary concentration of wealth and privilege.  Ominous environmental threats loom. The architecture of international relations designed in the mid-1940’s has become obsolete.   Research Design: To design this commentary about the prospects of the evaluation discipline, the author drew on his personal experience as evaluation academic, international development practitioner, manager of the World Bank’s Independent Evaluation Group for two consecutive five-year terms and senior independent evaluation adviser to governments and international development agencies.   Intervention: As an intervention, this article adds value to evaluation theory and practice by showing why and how the Popper/Campbell mandate for evaluation needs to be upgraded to protect the public interest in a new operating environment.  Specifically, Popper’s piecemeal social experimentation concept should be refined to forge links between small scale experiments and the broader fabric of society. In addition, the ambiguity regarding the relationship between the Open Society and evaluation should be lifted through a reconsideration of the democratic evaluation model.   Data Collection and Analysis: The author conducted an extensive review of the literature and consulted with a wide range of evaluation thinkers to examine the extent to which Popper’s philosophy remains relevant to the evaluation discipline.   Findings: Popper’s Open Society ideas aimed at avoiding the rise and perpetuation of autocracy and remain highly relevant. But the current threats to democracy call for a more ambitious and detailed remit for the evaluation occupation. Beyond the promotion of evaluation in democracy and of democracy in evaluation, evaluation for democracy should be pursued. This implies putting value, ethics, and the public interest at the very center of the evaluation occupation; breaking free of Popper’s parsimonious piecemeal social engineering concept to inform systemic social reform; bringing peace to a methodologically divided house; systematic mixing of evaluation methods and models; and the promotion of evaluation independence through professionalization.   Keywords: democracy; experimentation; falsification; paradigm wars; piecemeal social engineering. &nbsp

Evolutionary aesthetics as a meeting point of philosophy and biology

Metaphysics, or the knowledge of what there is, has been traditionally placed at the pinnacle of philosophical hierarchy. It was followed by theory of knowledge, or epistemology. Practical knowledge of proper modes of conduct, ethics, came third, followed by aesthetics, treated usually in a marginal way as having to do only with the perception of the beautiful. The hierarchy of philosophical disciplines has recently undergone a substantial transformation. As a result, ethics has assumed a central role. The aim of this paper is to suggest that the hierarchy of philosophical disciplines is not yet complete and that one further step needs to be taken. According to the claim advocated here, it is not metaphysics, epistemology or ethics, but aesthetics that is the first and foremost of all philosophical disciplines. This claim is argued for by references to findings of evolutionary aesthetics, especially to Charles Darwin's idea of sexual selection as elaborated in The Descent of Man. I also argue that Darwinian approach to morality is, and should be, derivable from an Darwinian aesthetics which lies at the core of his conception of sexual selection