Matching Items (78)
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As technological advancements in silicon, sensors, and actuation continue, the development of robotic swarms is shifting from the domain of science fiction to reality. Many swarm applications, such as environmental monitoring, precision agriculture, disaster response, and lunar prospecting, will require controlling numerous robots with limited capabilities and information to redistribute

As technological advancements in silicon, sensors, and actuation continue, the development of robotic swarms is shifting from the domain of science fiction to reality. Many swarm applications, such as environmental monitoring, precision agriculture, disaster response, and lunar prospecting, will require controlling numerous robots with limited capabilities and information to redistribute among multiple states, such as spatial locations or tasks. A scalable control approach is to program the robots with stochastic control policies such that the robot population in each state evolves according to a mean-field model, which is independent of the number and identities of the robots. Using this model, the control policies can be designed to stabilize the swarm to the target distribution. To avoid the need to reprogram the robots for different target distributions, the robot control policies can be defined to depend only on the presence of a “leader” agent, whose control policy is designed to guide the swarm to a particular distribution. This dissertation presents a novel deep reinforcement learning (deep RL) approach to designing control policies that redistribute a swarm as quickly as possible over a strongly connected graph, according to a mean-field model in the form of the discrete-time Kolmogorov forward equation. In the leader-based strategies, the leader determines its next action based on its observations of robot populations and shepherds the swarm over the graph by probabilistically repelling nearby robots. The scalability of this approach with the swarm size is demonstrated with leader control policies that are designed using two tabular Temporal-Difference learning algorithms, trained on a discretization of the swarm distribution. To improve the scalability of the approach with robot population and graph size, control policies for both leader-based and leaderless strategies are designed using an actor-critic deep RL method that is trained on the swarm distribution predicted by the mean-field model. In the leaderless strategy, the robots’ control policies depend only on their local measurements of nearby robot populations. The control approaches are validated for different graph and swarm sizes in numerical simulations, 3D robot simulations, and experiments on a multi-robot testbed.
ContributorsKakish, Zahi Mousa (Author) / Berman, Spring (Thesis advisor) / Yong, Sze Zheng (Committee member) / Marvi, Hamid (Committee member) / Pavlic, Theodore (Committee member) / Pratt, Stephen (Committee member) / Ben Amor, Hani (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Despite theoretical models predicting that signals should only evolve if they convey honest information, dishonest signals may persist. Interestingly, crustaceans have been crucial in furthering biologists understanding of how and why dishonest signals persist; because many crustaceans wield claws that function as dishonest signals. For example, male fiddler crabs have

Despite theoretical models predicting that signals should only evolve if they convey honest information, dishonest signals may persist. Interestingly, crustaceans have been crucial in furthering biologists understanding of how and why dishonest signals persist; because many crustaceans wield claws that function as dishonest signals. For example, male fiddler crabs have claws that grow to large sizes but are incapable of inflicting severe damage to opponents, thus acting as a dishonest signal of their strength. Although initial work suggested that dishonest signaling was common throughout Crustacea, biologists understanding of the generality of dishonest communication is lacking. To resolve these issues, I combined morphological, behavioral, and comparative studies to investigate whether crayfish engage in dishonest communication. First, I found that regenerated claws in virile crayfish (Faxonius virilis) produce 40% weaker pinching forces compared to original claws. These results suggest that claw regeneration in crayfish may be the functional mechanism that produces dishonest signals. Second, I conducted two studies that investigated what traits determine dominance in staged contests; one on intrasexual contests in both male and female F. virilis, and a second between intra- and interspecific contests between male F. virilis and male red swamp crayfish (Procambarus clarkii). In both studies, I did not find support the hypothesis that large but weak claws function as dishonest signals; because claw size did not predict the outcome of signaling interactions and claw strength did not predict the outcome of physical fights. Lastly, I conducted a comparative study between six species of crayfish — three stream-dwelling species that use their claws as weapons and signals, and three burrowing species that use their claws for excavating burrows. Despite all six species possessing claws that unreliably predicted claw strength, I found no support for the hypothesis that their claws function as dishonest signals in any of these species. Thus, my dissertation results suggest that despite having claws that unreliably predict their strength, such unreliable signals do not equate to dishonest signals. Altogether, my work highlights the importance of collecting behavioral data in studies of dishonest communication and stresses the importance of separating unreliable signals from dishonest signals.
ContributorsGraham, Zackary (Author) / Angilletta, Michael (Thesis advisor) / Martins, Emilia (Committee member) / McGraw, Kevin (Committee member) / Pratt, Stephen (Committee member) / Wilson, Robbie (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Getting clear about what behavioral scientists mean when they invoke content presupposing concepts, like information, is necessary for understanding how humanity’s own behavioral capacities do or do not relate to those of non-human animals. Yet, producing a general naturalistic definition for representational content has proven notoriously difficult. Some have argued

Getting clear about what behavioral scientists mean when they invoke content presupposing concepts, like information, is necessary for understanding how humanity’s own behavioral capacities do or do not relate to those of non-human animals. Yet, producing a general naturalistic definition for representational content has proven notoriously difficult. Some have argued that Claude Shannon’s formal, mathematically defined notion of information is the proper starting point for building a biological theory of content. Others have sought to define content presupposing concepts in terms of the historical selection processes that drive evolution. However, neither approach has produced definitions that capture the way successful researchers in the behavioral sciences use content-presupposing concepts. In this dissertation, I examine an ethological tradition of insect navigation research that has consistently ascribed content to insects. To clarify the meaning of such ascriptions, I analyze the practices scientists use to justify new attributions of content and the way new attributions of content guide scientists’ future research activities. In chapter 1, I examine a series of insect navigation experiments performed in 2006–2007 that led to a novel ascription of content. I argue that researchers ascribe content to insects’ navigation behaviors when those behaviors reliably accomplish a difficult goal-directed function. I also argue that ascriptions of content help researchers achieve their epistemic aims by guiding hypothesis formation and aiding comparative theorizing. In chapter 2, I trace the history of the experimental strategy analyzed above back to the work of Karl von Frisch in the early 20th century. I argue that von Frisch has a complicated and understudied relationship to the discipline of ethology. I support that argument by highlighting features of von Frisch’s research that both comported with and differed from the program of classical ethology. In chapter 3, I examine the cognitive map debate in insects. I argue that the debate stems from competing research groups’ endorsement of different norms for justifying claims about the dynamics of representational contents. I then situate these different norms historically to show how the cognitive map debate is a continuation of longstanding divisions within the history of animal behavior research.
ContributorsDhein, Kelle (Author) / Sterner, Beckett (Thesis advisor) / Maienschein, Jane (Committee member) / Allen, Colin (Committee member) / Pratt, Stephen (Committee member) / Laubichler, Manfred (Committee member) / Arizona State University (Publisher)
Created2021
Description

Background: Meiotic recombination has traditionally been explained based on the structural requirement to stabilize homologous chromosome pairs to ensure their proper meiotic segregation. Competing hypotheses seek to explain the emerging findings of significant heterogeneity in recombination rates within and between genomes, but intraspecific comparisons of genome-wide recombination patterns are rare.

Background: Meiotic recombination has traditionally been explained based on the structural requirement to stabilize homologous chromosome pairs to ensure their proper meiotic segregation. Competing hypotheses seek to explain the emerging findings of significant heterogeneity in recombination rates within and between genomes, but intraspecific comparisons of genome-wide recombination patterns are rare. The honey bee (Apis mellifera) exhibits the highest rate of genomic recombination among multicellular animals with about five cross-over events per chromatid.

Results: Here, we present a comparative analysis of recombination rates across eight genetic linkage maps of the honey bee genome to investigate which genomic sequence features are correlated with recombination rate and with its variation across the eight data sets, ranging in average marker spacing ranging from 1 Mbp to 120 kbp. Overall, we found that GC content explained best the variation in local recombination rate along chromosomes at the analyzed 100 kbp scale. In contrast, variation among the different maps was correlated to the abundance of microsatellites and several specific tri- and tetra-nucleotides.

Conclusions: The combined evidence from eight medium-scale recombination maps of the honey bee genome suggests that recombination rate variation in this highly recombining genome might be due to the DNA configuration instead of distinct sequence motifs. However, more fine-scale analyses are needed. The empirical basis of eight differing genetic maps allowed for robust conclusions about the correlates of the local recombination rates and enabled the study of the relation between DNA features and variability in local recombination rates, which is particularly relevant in the honey bee genome with its exceptionally high recombination rate.

ContributorsRoss, Caitlin R. (Author) / DeFelice, Dominick S. (Author) / Hunt, Greg J. (Author) / Ihle, Kate (Author) / Amdam, Gro (Author) / Rueppell, Olav (Author) / College of Liberal Arts and Sciences (Contributor)
Created2015-02-21
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Description

In this paper, we present an approach to designing decentralized robot control policies that mimic certain microscopic and macroscopic behaviors of ants performing collective transport tasks. In prior work, we used a stochastic hybrid system model to characterize the observed team dynamics of ant group retrieval of a rigid load.

In this paper, we present an approach to designing decentralized robot control policies that mimic certain microscopic and macroscopic behaviors of ants performing collective transport tasks. In prior work, we used a stochastic hybrid system model to characterize the observed team dynamics of ant group retrieval of a rigid load. We have also used macroscopic population dynamic models to design enzyme-inspired stochastic control policies that allocate a robotic swarm around multiple boundaries in a way that is robust to environmental variations. Here, we build on this prior work to synthesize stochastic robot attachment–detachment policies for tasks in which a robotic swarm must achieve non-uniform spatial distributions around multiple loads and transport them at a constant velocity. Three methods are presented for designing robot control policies that replicate the steady-state distributions, transient dynamics, and fluxes between states that we have observed in ant populations during group retrieval. The equilibrium population matching method can be used to achieve a desired transport team composition as quickly as possible; the transient matching method can control the transient population dynamics of the team while driving it to the desired composition; and the rate matching method regulates the rates at which robots join and leave a load during transport. We validate our model predictions in an agent-based simulation, verify that each controller design method produces successful transport of a load at a regulated velocity, and compare the advantages and disadvantages of each method.

ContributorsWilson, Sean (Author) / Pavlic, Theodore (Author) / Kumar, Ganesh (Author) / Buffin, Aurelie (Author) / Pratt, Stephen (Author) / Berman, Spring (Author) / Ira A. Fulton Schools of Engineering (Contributor)
Created2014-12-01
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Honeybee workers are essentially sterile female helpers that make up the majority of individuals in a colony. Workers display a marked change in physiology when they transition from in-nest tasks to foraging. Recent technological advances have made it possible to unravel the metabolic modifications associated with this transition. Previous studies

Honeybee workers are essentially sterile female helpers that make up the majority of individuals in a colony. Workers display a marked change in physiology when they transition from in-nest tasks to foraging. Recent technological advances have made it possible to unravel the metabolic modifications associated with this transition. Previous studies have revealed extensive remodeling of brain, thorax, and hypopharyngeal gland biochemistry. However, data on changes in the abdomen is scarce. To narrow this gap we investigated the proteomic composition of abdominal tissue in the days typically preceding the onset of foraging in honeybee workers.

In order to get a broader representation of possible protein dynamics, we used workers of two genotypes with differences in the age at which they initiate foraging. This approach was combined with RNA interference-mediated downregulation of an insulin/insulin-like signaling component that is central to foraging behavior, the insulin receptor substrate (irs), and with measurements of glucose and lipid levels.
Our data provide new insight into the molecular underpinnings of phenotypic plasticity in the honeybee, invoke parallels with vertebrate metabolism, and support an integrated and irs-dependent association of carbohydrate and lipid metabolism with the transition from in-nest tasks to foraging.

ContributorsChan, Queenie W. T. (Author) / Mutti, Navdeep (Author) / Foster, Leonard J. (Author) / Kocher, Sarah D. (Author) / Amdam, Gro (Author) / Wolschin, Florian (Author) / College of Liberal Arts and Sciences (Contributor)
Created2011-09-28
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Description

Recent advancements in genomics provide new tools for evolutionary ecological research. The paper wasp genus Polistes is a model for social insect evolution and behavioral ecology. We developed RNA interference (RNAi)-mediated gene silencing to explore proposed connections between expression of hexameric storage proteins and worker vs. gyne (potential future foundress)

Recent advancements in genomics provide new tools for evolutionary ecological research. The paper wasp genus Polistes is a model for social insect evolution and behavioral ecology. We developed RNA interference (RNAi)-mediated gene silencing to explore proposed connections between expression of hexameric storage proteins and worker vs. gyne (potential future foundress) castes in naturally-founded colonies of P. metricus. We extended four fragments of putative hexamerin-encoding P. metricus transcripts acquired from a previous study and fully sequenced a gene that encodes Hexamerin 2, one of two proposed hexameric storage proteins of P. metricus. MALDI-TOF/TOF, LC-MSMS, deglycosylation, and detection of phosphorylation assays showed that the two putative hexamerins diverge in peptide sequence and biochemistry. We targeted the hexamerin 2 gene in 5th (last)-instar larvae by feeding RNAi-inducing double-stranded hexamerin 2 RNA directly to larvae in naturally-founded colonies in the field. Larval development and adult traits were not significantly altered in hexamerin 2 knockdowns, but there were suggestive trends toward increased developmental time and less developed ovaries, which are gyne characteristics. By demonstrating how data acquisition from 454/Roche pyrosequencing can be combined with biochemical and proteomics assays and how RNAi can be deployed successfully in field experiments on Polistes, our results pave the way for functional genomic research that can contribute significantly to learning the interactions of environment, development, and the roles they play in paper wasp evolution and behavioral ecology.

ContributorsHunt, James H. (Author) / Mutti, Navdeep (Author) / Havukainen, Heli (Author) / Henshaw, Michael T. (Author) / Amdam, Gro (Author) / College of Liberal Arts and Sciences (Contributor)
Created2011-11-01
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Background: Phosphatase and TENsin (PTEN) homolog is a negative regulator that takes part in IIS (insulin/insulin-like signaling) and Egfr (epidermal growth factor receptor) activation in Drosophila melanogaster. IIS and Egfr signaling events are also involved in the developmental process of queen and worker differentiation in honey bees (Apis mellifera). Here, we

Background: Phosphatase and TENsin (PTEN) homolog is a negative regulator that takes part in IIS (insulin/insulin-like signaling) and Egfr (epidermal growth factor receptor) activation in Drosophila melanogaster. IIS and Egfr signaling events are also involved in the developmental process of queen and worker differentiation in honey bees (Apis mellifera). Here, we characterized the bee PTEN gene homologue for the first time and begin to explore its potential function during bee development and adult life.

Results: Honey bee PTEN is alternatively spliced, resulting in three splice variants. Next, we show that the expression of PTEN can be down-regulated by RNA interference (RNAi) in the larval stage, when female caste fate is determined. Relative to controls, we observed that RNAi efficacy is dependent on the amount of PTEN dsRNA that is delivered to larvae. For larvae fed queen or worker diets containing a high amount of PTEN dsRNA, PTEN knockdown was significant at a whole-body level but lethal. A lower dosage did not result in a significant gene down-regulation. Finally, we compared same-aged adult workers with different behavior: nursing vs. foraging. We show that between nurses and foragers, PTEN isoforms were differentially expressed within brain, ovary and fat body tissues. All isoforms were expressed at higher levels in the brain and ovaries of the foragers. In fat body, isoform B was expressed at higher level in the nurse bees.

Conclusion: Our results suggest that PTEN plays a central role during growth and development in queen- and worker-destined honey bees. In adult workers, moreover, tissue-specific patterns of PTEN isoform expression are correlated with differences in complex division of labor between same-aged individuals. Therefore, we propose that knowledge on the roles of IIS and Egfr activity in developmental and behavioral control may increase through studies of how PTEN functions can impact bee social phenotypes.

ContributorsMutti, Navdeep (Author) / Wang, Ying (Author) / Kaftanoglu, Osman (Author) / Amdam, Gro (Author) / College of Liberal Arts and Sciences (Contributor)
Created2011-07-14
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Description

Background: Juvenile hormone (JH) has been demonstrated to control adult lifespan in a number of non-model insects where surgical removal of the corpora allata eliminates the hormone’s source. In contrast, little is known about how juvenile hormone affects adult Drosophila melanogaster. Previous work suggests that insulin signaling may modulate Drosophila aging

Background: Juvenile hormone (JH) has been demonstrated to control adult lifespan in a number of non-model insects where surgical removal of the corpora allata eliminates the hormone’s source. In contrast, little is known about how juvenile hormone affects adult Drosophila melanogaster. Previous work suggests that insulin signaling may modulate Drosophila aging in part through its impact on juvenile hormone titer, but no data yet address whether reduction of juvenile hormone is sufficient to control Drosophila life span. Here we adapt a genetic approach to knock out the corpora allata in adult Drosophila melanogaster and characterize adult life history phenotypes produced by reduction of juvenile hormone. With this system we test potential explanations for how juvenile hormone modulates aging.

Results: A tissue specific driver inducing an inhibitor of a protein phosphatase was used to ablate the corpora allata while permitting normal development of adult flies. Corpora allata knockout adults had greatly reduced fecundity, inhibited oogenesis, impaired adult fat body development and extended lifespan. Treating these adults with the juvenile hormone analog methoprene restored all traits toward wildtype. Knockout females remained relatively long-lived even when crossed into a genotype that blocked all egg production. Dietary restriction further extended the lifespan of knockout females. In an analysis of expression profiles of knockout females in fertile and sterile backgrounds, about 100 genes changed in response to loss of juvenile hormone independent of reproductive state.

Conclusions: Reduced juvenile hormone alone is sufficient to extend the lifespan of Drosophila melanogaster. Reduced juvenile hormone limits reproduction by inhibiting the production of yolked eggs, and this may arise because juvenile hormone is required for the post-eclosion development of the vitellogenin-producing adult fat body. Our data do not support a mechanism for juvenile hormone control of longevity simply based on reducing the physiological costs of egg production. Nor does the longevity benefit appear to function through mechanisms by which dietary restriction extends longevity. We identify transcripts that change in response to juvenile hormone independent of reproductive state and suggest these represent somatically expressed genes that could modulate how juvenile hormone controls persistence and longevity.

ContributorsYamamoto, Rochelle (Author) / Bai, Hua (Author) / Dolezal, Adam (Author) / Amdam, Gro (Author) / Tatar, Marc (Author) / College of Liberal Arts and Sciences (Contributor)
Created2013-07-17
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Description

Background: Gene bodies are the most evolutionarily conserved targets of DNA methylation in eukaryotes. However, the regulatory functions of gene body DNA methylation remain largely unknown. DNA methylation in insects appears to be primarily confined to exons. Two recent studies in Apis mellifera (honeybee) and Nasonia vitripennis (jewel wasp) analyzed transcription

Background: Gene bodies are the most evolutionarily conserved targets of DNA methylation in eukaryotes. However, the regulatory functions of gene body DNA methylation remain largely unknown. DNA methylation in insects appears to be primarily confined to exons. Two recent studies in Apis mellifera (honeybee) and Nasonia vitripennis (jewel wasp) analyzed transcription and DNA methylation data for one gene in each species to demonstrate that exon-specific DNA methylation may be associated with alternative splicing events. In this study we investigated the relationship between DNA methylation, alternative splicing, and cross-species gene conservation on a genome-wide scale using genome-wide transcription and DNA methylation data.

Results: We generated RNA deep sequencing data (RNA-seq) to measure genome-wide mRNA expression at the exon- and gene-level. We produced a de novo transcriptome from this RNA-seq data and computationally predicted splice variants for the honeybee genome. We found that exons that are included in transcription are higher methylated than exons that are skipped during transcription. We detected enrichment for alternative splicing among methylated genes compared to unmethylated genes using fisher’s exact test. We performed a statistical analysis to reveal that the presence of DNA methylation or alternative splicing are both factors associated with a longer gene length and a greater number of exons in genes. In concordance with this observation, a conservation analysis using BLAST revealed that each of these factors is also associated with higher cross-species gene conservation.

Conclusions: This study constitutes the first genome-wide analysis exhibiting a positive relationship between exon-level DNA methylation and mRNA expression in the honeybee. Our finding that methylated genes are enriched for alternative splicing suggests that, in invertebrates, exon-level DNA methylation may play a role in the construction of splice variants by positively influencing exon inclusion during transcription. The results from our cross-species homology analysis suggest that DNA methylation and alternative splicing are genetic mechanisms whose utilization could contribute to a longer gene length and a slower rate of gene evolution.

ContributorsFlores, Kevin (Author) / Wolschin, Florian (Author) / Corneveaux, Jason J. (Author) / Allen, April N. (Author) / Huentelman, Matthew J. (Author) / Amdam, Gro (Author) / College of Liberal Arts and Sciences (Contributor)
Created2012-09-15