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Description
For over a century, researchers have been investigating collective cognition, in which a group of individuals together process information and act as a single cognitive unit. However, I still know little about circumstances under which groups achieve better (or worse) decisions than individuals. My dissertation research directly addressed this longstanding

For over a century, researchers have been investigating collective cognition, in which a group of individuals together process information and act as a single cognitive unit. However, I still know little about circumstances under which groups achieve better (or worse) decisions than individuals. My dissertation research directly addressed this longstanding question, using the house-hunting ant Temnothorax rugatulus as a model system. Here I applied concepts and methods developed in psychology not only to individuals but also to colonies in order to investigate differences of their cognitive abilities. This approach is inspired by the superorganism concept, which sees a tightly integrated insect society as the analog of a single organism. I combined experimental manipulations and models to elucidate the emergent processes of collective cognition. My studies show that groups can achieve superior cognition by sharing the burden of option assessment among members and by integrating information from members using positive feedback. However, the same positive feedback can lock the group into a suboptimal choice in certain circumstances. Although ants are obligately social, my results show that they can be isolated and individually tested on cognitive tasks. In the future, this novel approach will help the field of animal behavior move towards better understanding of collective cognition.
ContributorsSasaki, Takao (Author) / Pratt, Stephen C (Thesis advisor) / Amazeen, Polemnia (Committee member) / Liebig, Jürgen (Committee member) / Janssen, Marco (Committee member) / Fewell, Jennifer (Committee member) / Hölldobler, Bert (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The spread of invasive species may be greatly affected by human responses to prior species spread, but models and estimation methods seldom explicitly consider human responses. I investigate the effects of management responses on estimates of invasive species spread rates. To do this, I create an agent-based simulation model of

The spread of invasive species may be greatly affected by human responses to prior species spread, but models and estimation methods seldom explicitly consider human responses. I investigate the effects of management responses on estimates of invasive species spread rates. To do this, I create an agent-based simulation model of an insect invasion across a county-level citrus landscape. My model provides an approximation of a complex spatial environment while allowing the "truth" to be known. The modeled environment consists of citrus orchards with insect pests dispersing among them. Insects move across the simulation environment infesting orchards, while orchard managers respond by administering insecticide according to analyst-selected behavior profiles and management responses may depend on prior invasion states. Dispersal data is generated in each simulation and used to calculate spread rate via a set of estimators selected for their predominance in the empirical literature. Spread rate is a mechanistic, emergent phenomenon measured at the population level caused by a suite of latent biological, environmental, and anthropogenic. I test the effectiveness of orchard behavior profiles on invasion suppression and evaluate the robustness of the estimators given orchard responses. I find that allowing growers to use future expectations of spread in management decisions leads to reduced spread rates. Acting in a preventative manner by applying insecticide before insects are actually present, orchards are able to lower spread rates more than by reactive behavior alone. Spread rates are highly sensitive to spatial configuration. Spatial configuration is hardly a random process, consisting of many latent factors often not accounted for in spread rate estimation. Not considering these factors may lead to an omitted variables bias and skew estimation results. The ability of spread rate estimators to predict future spread varies considerably between estimators, and with spatial configuration, invader biological parameters, and orchard behavior profile. The model suggests that understanding the latent factors inherent to dispersal is important for selecting phenomenological models of spread and interpreting estimation results. This indicates a need for caution when evaluating spread. Although standard practice, current empirical estimators may both over- and underestimate spread rate in the simulation.
ContributorsShanafelt, David William (Author) / Fenichel, Eli P (Thesis advisor) / Richards, Timothy (Committee member) / Janssen, Marco (Committee member) / Arizona State University (Publisher)
Created2012
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DescriptionThis paper provides an analysis of the differences in impacts made by companies that promote their sustainability efforts. A comparison of companies reveals that the ones with greater supply chain influence and larger consumer bases can make more concrete progress in terms of accomplishment for the sustainability realm.
ContributorsBeaubien, Courtney Lynn (Author) / Anderies, John (Thesis director) / Allenby, Brad (Committee member) / Janssen, Marco (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2013-05
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Description

The evolution of cooperation is a fundamental problem in biology, especially for non-relatives, where indirect fitness benefits cannot counter within-group inequalities. Multilevel selection models show how cooperation can evolve if it generates a group-level advantage, even when cooperators are disadvantaged within their group. This allows the possibility of group selection,

The evolution of cooperation is a fundamental problem in biology, especially for non-relatives, where indirect fitness benefits cannot counter within-group inequalities. Multilevel selection models show how cooperation can evolve if it generates a group-level advantage, even when cooperators are disadvantaged within their group. This allows the possibility of group selection, but few examples have been described in nature. Here we show that group selection can explain the evolution of cooperative nest founding in the harvester ant Pogonomyrmex californicus. Through most of this species’ range, colonies are founded by single queens, but in some populations nests are instead founded by cooperative groups of unrelated queens. In mixed groups of cooperative and single-founding queens, we found that aggressive individuals had a survival advantage within their nest, but foundress groups with such non-cooperators died out more often than those with only cooperative members. An agent-based model shows that the between-group advantage of the cooperative phenotype drives it to fixation, despite its within-group disadvantage, but only when population density is high enough to make between-group competition intense. Field data show higher nest density in a population where cooperative founding is common, consistent with greater density driving the evolution of cooperative foundation through group selection.

ContributorsShaffer, Zachary (Author) / Sasaki, Takao (Author) / Haney, Brian (Author) / Janssen, Marco (Author) / Pratt, Stephen (Author) / Fewell, Jennifer (Author) / College of Liberal Arts and Sciences (Contributor)
Created2016-07-28
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Description
Climate change presents the urgent need for effective sustainable water management that is capable of preserving natural resources while maintaining economical stability. States like California rely heavily on groundwater pumping for agricultural use, contributing to land subsidence and insufficient returns to water resources. The recent California drought has impacted agricultural

Climate change presents the urgent need for effective sustainable water management that is capable of preserving natural resources while maintaining economical stability. States like California rely heavily on groundwater pumping for agricultural use, contributing to land subsidence and insufficient returns to water resources. The recent California drought has impacted agricultural production of certain crops. In this thesis, we present an agent-based model of farmers adapting to drought conditions by making crop choice decisions, much like the decisions Californian farmers have made. We use the Netlogo platform to capture the 2D spatial view of an agricultural system with changes in annual rainfall due to drought conditions. The goal of this model is to understand some of the simple rules farmers may follow to self-govern their consumption of a water resource. Farmer agents make their crop decisions based on deficit irrigation crop production function and a net present value discount rate. The farmers choose between a thirsty crop with a high production cost and a dry crop with a low production cost. Simulations results show that farmers switch crops in accordance with limited water and land resources. Farmers can maintain profit and yield by following simple rules of crop switching based on future yields and optimal irrigation. In drought conditions, individual agents expecting lower annual rainfall were able to increase their total profits. The maintenance of crop yield and profit is evidence of successful adaptation when farmers switch to crops that require less water.
ContributorsGokool, Rachael Shanta (Author) / Janssen, Marco (Thesis director) / Eakin, Hallie (Committee member) / School of Human Evolution and Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
Background: National and international strategies to increase physical activity emphasize environmental and policy changes that can have widespread and long-lasting impact. Evidence from multiple countries using comparable methods is required to strengthen the evidence base for such initiatives. Because some environment and policy changes could have generalizable effects and others

Background: National and international strategies to increase physical activity emphasize environmental and policy changes that can have widespread and long-lasting impact. Evidence from multiple countries using comparable methods is required to strengthen the evidence base for such initiatives. Because some environment and policy changes could have generalizable effects and others may depend on each country's context, only international studies using comparable methods can identify the relevant differences. Methods: Currently 12 countries are participating in the International Physical Activity and the Environment Network (IPEN) study. The IPEN Adult study design involves recruiting adult participants from neighborhoods with wide variations in environmental walkability attributes and socioeconomic status (SES). Results: Eleven of twelve countries are providing accelerometer data and 11 are providing GIS data. Current projections indicate that 14,119 participants will provide survey data on built environments and physical activity and 7145 are likely to provide objective data on both the independent and dependent variables. Though studies are highly comparable, some adaptations are required based on the local context. Conclusions: This study was designed to inform evidence-based international and country-specific physical activity policies and interventions to help prevent obesity and other chronic diseases that are high in developed countries and growing rapidly in developing countries.
ContributorsKerr, Jacqueline (Author) / Sallis, James F. (Author) / Owen, Neville (Author) / De Bourdeaudhuij, Ilse (Author) / Cerin, Ester (Author) / Sugiyama, Takemi (Author) / Reis, Rodrigo (Author) / Sarmiento, Olga (Author) / Froemel, Karel (Author) / Mitas, Josef (Author) / Troelsen, Jens (Author) / Christiansen, Lars Breum (Author) / Macfarlane, Duncan (Author) / Salvo, Deborah (Author) / Schofield, Grant (Author) / Badland, Hannah (Author) / Guillen-Grima, Francisco (Author) / Aguinaga-Ontoso, Ines (Author) / Davey, Rachel (Author) / Bauman, Adrian (Author) / Saelens, Brian (Author) / Riddoch, Chris (Author) / Ainsworth, Barbara (Author) / Pratt, Michael (Author) / Schmidt, Tom (Author) / Frank, Lawrence (Author) / Adams, Marc (Author) / Conway, Terry (Author) / Cain, Kelli (Author) / Van Dyck, Delfien (Author) / Bracy, Nicole (Author) / College of Health Solutions (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2013
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Description
Coffee is an important link between the United States and Latin America and an important part of Latin America’s culture and economy. This paper looks at the similarities and differences between coffee organizations in Colombia, Ecuador, Peru, and Guatemala. Colombia has the strongest coffee organizations with the most political power.

Coffee is an important link between the United States and Latin America and an important part of Latin America’s culture and economy. This paper looks at the similarities and differences between coffee organizations in Colombia, Ecuador, Peru, and Guatemala. Colombia has the strongest coffee organizations with the most political power. Guatemala and Peru, to a lesser extent, have well organized and powerful organizations that make up their industry. However, Ecuador has a significantly less organized organization. At their core, each country has a similar structure. There is one organization on the national level that watches out for the industry as a whole. Underneath that, there are smaller, often regional organizations made up of cooperatives pooling their resources for export. They function in similar ways as the national organizations, but have less reach. At the bottom, there are individual cooperatives and independent farmers. These cooperatives do not have much reach or connection to international markets.
ContributorsChabin, James Edward (Author) / Janssen, Marco (Thesis director) / Taylor, Keith (Committee member) / School of Sustainability (Contributor) / School of International Letters and Cultures (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Description
Background
Increasing empirical evidence supports associations between neighborhood environments and physical activity. However, since most studies were conducted in a single country, particularly western countries, the generalizability of associations in an international setting is not well understood. The current study examined whether associations between perceived attributes of neighborhood environments and physical

Background
Increasing empirical evidence supports associations between neighborhood environments and physical activity. However, since most studies were conducted in a single country, particularly western countries, the generalizability of associations in an international setting is not well understood. The current study examined whether associations between perceived attributes of neighborhood environments and physical activity differed by country.
Methods
Population representative samples from 11 countries on five continents were surveyed using comparable methodologies and measurement instruments. Neighborhood environment × country interactions were tested in logistic regression models with meeting physical activity recommendations as the outcome, adjusted for demographic characteristics. Country-specific associations were reported.
Results
Significant neighborhood environment attribute × country interactions implied some differences across countries in the association of each neighborhood attribute with meeting physical activity recommendations. Across the 11 countries, land-use mix and sidewalks had the most consistent associations with physical activity. Access to public transit, bicycle facilities, and low-cost recreation facilities had some associations with physical activity, but with less consistency across countries. There was little evidence supporting the associations of residential density and crime-related safety with physical activity in most countries.
Conclusion
There is evidence of generalizability for the associations of land use mix, and presence of sidewalks with physical activity. Associations of other neighborhood characteristics with physical activity tended to differ by country. Future studies should include objective measures of neighborhood environments, compare psychometric properties of reports across countries, and use better specified models to further understand the similarities and differences in associations across countries.
ContributorsDing, Ding (Author) / Adams, Marc (Author) / Sallis, James F. (Author) / Norman, Gregory J. (Author) / Hovell, Melbourn F. (Author) / Chambers, Christina D. (Author) / Hofstetter, C. Richard (Author) / Bowles, Heather R. (Author) / Hagstromer, Maria (Author) / Craig, Cora L. (Author) / Fernando Gomez, Luis (Author) / De Bourdeaudhuij, Ilse (Author) / Macfarlane, Duncan J. (Author) / Ainsworth, Barbara (Author) / Bergman, Patrick (Author) / Bull, Fiona C. (Author) / Carr, Harriette (Author) / Klasson-Heggebo, Lena (Author) / Inoue, Shigeru (Author) / Murase, Norio (Author) / Matsudo, Sandra (Author) / Matsudo, Victor (Author) / McLean, Grant (Author) / Sjostrom, Michael (Author) / Tomten, Heidi (Author) / Lefevre, Johan (Author) / Volbekiene, Vida (Author) / Bauman, Adrian E. (Author) / College of Health Solutions (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2013-05-14
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Description
Background
Neighborhood environment studies of physical activity (PA) have been mainly single-country focused. The International Prevalence Study (IPS) presented a rare opportunity to examine neighborhood features across countries. The purpose of this analysis was to: 1) detect international neighborhood typologies based on participants’ response patterns to an environment survey and 2)

Background
Neighborhood environment studies of physical activity (PA) have been mainly single-country focused. The International Prevalence Study (IPS) presented a rare opportunity to examine neighborhood features across countries. The purpose of this analysis was to: 1) detect international neighborhood typologies based on participants’ response patterns to an environment survey and 2) to estimate associations between neighborhood environment patterns and PA.
Methods
A Latent Class Analysis (LCA) was conducted on pooled IPS adults (N=11,541) aged 18 to 64 years old (mean=37.5 ±12.8 yrs; 55.6% women) from 11 countries including Belgium, Brazil, Canada, Colombia, Hong Kong, Japan, Lithuania, New Zealand, Norway, Sweden, and the U.S. This subset used the Physical Activity Neighborhood Environment Survey (PANES) that briefly assessed 7 attributes within 10–15 minutes walk of participants’ residences, including residential density, access to shops/services, recreational facilities, public transit facilities, presence of sidewalks and bike paths, and personal safety. LCA derived meaningful subgroups from participants’ response patterns to PANES items, and participants were assigned to neighborhood types. The validated short-form International Physical Activity Questionnaire (IPAQ) measured likelihood of meeting the 150 minutes/week PA guideline. To validate derived classes, meeting the guideline either by walking or total PA was regressed on neighborhood types using a weighted generalized linear regression model, adjusting for gender, age and country.
Results
A 5-subgroup solution fitted the dataset and was interpretable. Neighborhood types were labeled, “Overall Activity Supportive (52% of sample)”, “High Walkable and Unsafe with Few Recreation Facilities (16%)”, “Safe with Active Transport Facilities (12%)”, “Transit and Shops Dense with Few Amenities (15%)”, and “Safe but Activity Unsupportive (5%)”. Country representation differed by type (e.g., U.S. disproportionally represented “Safe but Activity Unsupportive”). Compared to the Safe but Activity Unsupportive, two types showed greater odds of meeting PA guideline for walking outcome (High Walkable and Unsafe with Few Recreation Facilities, OR= 2.26 (95% CI 1.18-4.31); Overall Activity Supportive, OR= 1.90 (95% CI 1.13-3.21). Significant but smaller odds ratios were also found for total PA.
Conclusions
Meaningful neighborhood patterns generalized across countries and explained practical differences in PA. These observational results support WHO/UN recommendations for programs and policies targeted to improve features of the neighborhood environment for PA.
ContributorsAdams, Marc (Author) / Ding, Ding (Author) / Sallis, James F. (Author) / Bowles, Heather R. (Author) / Ainsworth, Barbara (Author) / Bergman, Patrick (Author) / Bull, Fiona C. (Author) / Carr, Harriette (Author) / Craig, Cora L. (Author) / De Bourdeaudhuij, Ilse (Author) / Fernando Gomez, Luis (Author) / Hagstromer, Maria (Author) / Klasson-Heggebo, Lena (Author) / Inoue, Shigeru (Author) / Lefevre, Johan (Author) / Macfarlane, Duncan J. (Author) / Matsudo, Sandra (Author) / Matsudo, Victor (Author) / McLean, Grant (Author) / Murase, Norio (Author) / Sjostrom, Michael (Author) / Tomten, Heidi (Author) / Volbekiene, Vida (Author) / Bauman, Adrian (Author) / College of Health Solutions (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2013-03-07
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Description
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination

Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021