SAGA: A project to automate the management of software production systems

The project to automate the management of software production systems is described. The SAGA system is a software environment that is designed to support most of the software development activities that occur in a software lifecycle. The system can be configured to support specific software development applications using given programming languages, tools, and methodologies. Meta-tools are provided to ease configuration. Several major components of the SAGA system are completed to prototype form. The construction methods are described

‘Special agents’ trigger social waves in giant honeybees (Apis dorsata)

Giant honeybees (Apis dorsata) nest in the open and have therefore evolved a variety of defence strategies. Against predatory wasps, they produce highly coordinated Mexican wavelike cascades termed ‘shimmering’, whereby hundreds of bees flip their abdomens upwards. Although it is well known that shimmering commences at distinct spots on the nest surface, it is still unclear how shimmering is generated. In this study, colonies were exposed to living tethered wasps that were moved in front of the experimental nest. Temporal and spatial patterns of shimmering were investigated in and after the presence of the wasp. The numbers and locations of bees that participated in the shimmering were assessed, and those bees that triggered the waves were identified. The findings reveal that the position of identified trigger cohorts did not reflect the experimental path of the tethered wasp. Instead, the trigger centres were primarily arranged in the close periphery of the mouth zone of the nest, around those parts where the main locomotory activity occurs. This favours the ‘special-agents’ hypothesis that suggest that groups of specialized bees initiate the shimmering

Evolution of self-organized division of labor in a response threshold model

Division of labor in social insects is determinant to their ecological success. Recent models emphasize that division of labor is an emergent property of the interactions among nestmates obeying to simple behavioral rules. However, the role of evolution in shaping these rules has been largely neglected. Here, we investigate a model that integrates the perspectives of self-organization and evolution. Our point of departure is the response threshold model, where we allow thresholds to evolve. We ask whether the thresholds will evolve to a state where division of labor emerges in a form that fits the needs of the colony. We find that division of labor can indeed evolve through the evolutionary branching of thresholds, leading to workers that differ in their tendency to take on a given task. However, the conditions under which division of labor evolves depend on the strength of selection on the two fitness components considered: amount of work performed and on worker distribution over tasks. When selection is strongest on the amount of work performed, division of labor evolves if switching tasks is costly. When selection is strongest on worker distribution, division of labor is less likely to evolve. Furthermore, we show that a biased distribution (like 3:1) of workers over tasks is not easily achievable by a threshold mechanism, even under strong selection. Contrary to expectation, multiple matings of colony foundresses impede the evolution of specialization. Overall, our model sheds light on the importance of considering the interaction between specific mechanisms and ecological requirements to better understand the evolutionary scenarios that lead to division of labor in complex systems

Spatial effects, sampling errors, and task specialization in the honey bee

Task allocation patterns should depend on the spatial distribution of work within the nest, variation in task demand, and the movement patterns of workers, however, relatively little research has focused on these topics. This study uses a spatially explicit agent based model to determine whether such factors alone can generate biases in task performance at the individual level in the honey bees, Apis mellifera. Specialization (bias in task performance) is shown to result from strong sampling error due to localized task demand, relatively slow moving workers relative to nest size, and strong spatial variation in task demand. To date, specialization has been primarily interpreted with the response threshold concept, which is focused on intrinsic (typically genotypic) differences between workers. Response threshold variation and sampling error due to spatial effects are not mutually exclusive, however, and this study suggests that both contribute to patterns of task bias at the individual level. While spatial effects are strong enough to explain some documented cases of specialization; they are relatively short term and not explanatory for long term cases of specialization. In general, this study suggests that the spatial layout of tasks and fluctuations in their demand must be explicitly controlled for in studies focused on identifying genotypic specialists

Ontology-based end-user visual query formulation: Why, what, who, how, and which?

Value creation in an organisation is a time-sensitive and data-intensive process, yet it is often delayed and bounded by the reliance on IT experts extracting data for domain experts. Hence, there is a need for providing people who are not professional developers with the flexibility to pose relatively complex and ad hoc queries in an easy and intuitive way. In this respect, visual methods for query formulation undertake the challenge of making querying independent of users’ technical skills and the knowledge of the underlying textual query language and the structure of data. An ontology is more promising than the logical schema of the underlying data for guiding users in formulating queries, since it provides a richer vocabulary closer to the users’ understanding. However, on the one hand, today the most of world’s enterprise data reside in relational databases rather than triple stores, and on the other, visual query formulation has become more compelling due to ever-increasing data size and complexity—known as Big Data. This article presents and argues for ontology-based visual query formulation for end-users; discusses its feasibility in terms of ontology-based data access, which virtualises legacy relational databases as RDF, and the dimensions of Big Data; presents key conceptual aspects and dimensions, challenges, and requirements; and reviews, categorises, and discusses notable approaches and systems

Rapid Transition towards the Division of Labor via Evolution of Developmental Plasticity

A crucial step in several major evolutionary transitions is the division of labor between components of the emerging higher-level evolutionary unit. Examples include the separation of germ and soma in simple multicellular organisms, appearance of multiple cell types and organs in more complex organisms, and emergence of casts in eusocial insects. How the division of labor was achieved in the face of selfishness of lower-level units is controversial. I present a simple mathematical model describing the evolutionary emergence of the division of labor via developmental plasticity starting with a colony of undifferentiated cells and ending with completely differentiated multicellular organisms. I explore how the plausibility and the dynamics of the division of labor depend on its fitness advantage, mutation rate, costs of developmental plasticity, and the colony size. The model shows that the transition to differentiated multicellularity, which has happened many times in the history of life, can be achieved relatively easily. My approach is expandable in a number of directions including the emergence of multiple cell types, complex organs, or casts of eusocial insects

Ants in a Labyrinth: A Statistical Mechanics Approach to the Division of Labour

Division of labour (DoL) is a fundamental organisational principle in human societies, within virtual and robotic swarms and at all levels of biological organisation. DoL reaches a pinnacle in the insect societies where the most widely used model is based on variation in response thresholds among individuals, and the assumption that individuals and stimuli are well-mixed. Here, we present a spatially explicit model of DoL. Our model is inspired by Pierre de Gennes' 'Ant in a Labyrinth' which laid the foundations of an entire new field in statistical mechanics. We demonstrate the emergence, even in a simplified one-dimensional model, of a spatial patterning of individuals and a right-skewed activity distribution, both of which are characteristics of division of labour in animal societies. We then show using a two-dimensional model that the work done by an individual within an activity bout is a sigmoidal function of its response threshold. Furthermore, there is an inverse relationship between the overall stimulus level and the skewness of the activity distribution. Therefore, the difference in the amount of work done by two individuals with different thresholds increases as the overall stimulus level decreases. Indeed, spatial fluctuations of task stimuli are minimised at these low stimulus levels. Hence, the more unequally labour is divided amongst individuals, the greater the ability of the colony to maintain homeostasis. Finally, we show that the non-random spatial distribution of individuals within biological and social systems could be caused by indirect (stigmergic) interactions, rather than direct agent-to-agent interactions. Our model links the principle of DoL with principles in the statistical mechanics and provides testable hypotheses for future experiments

Group demography affects ant colony performance and individual speed of queen and worker aging

Background: The performance and fitness of social societies mainly depends on the efficiency of interactions between reproductive individuals and helpers. Helpers need to react to the group's requirements and to adjust their tasks accordingly, while the reproductive individual has to adjust its reproductive rate. Social insects provide a good system to study the interrelations between individual and group characteristics. In general, sterile workers focus on brood care and foraging while the queen lays eggs. Reproductive division of labor is determined by caste and not interchangeable as, e.g., in social mammals or birds. Hence, changing social and environmental conditions require a flexible response by each caste. In the ant Cardiocondyla obscurior, worker task allocation is based on age polyethism, with young workers focusing on brood care and old workers on foraging. Here, we examine how group age demography affects colony performance and fitness in colonies consisting of only old or young workers and a single old or young queen. We hypothesized that both groups will be fully functional, but that the forced task shift affects the individuals' performance. Moreover, we expected reduced worker longevity in groups with only young workers due to precocious foraging but no effect on queen longevity depending on group composition. Results: Neither the performance of queens nor that of workers declined strongly with time per se, but offspring number and weight were influenced by queen age and the interaction between queen and worker age. Individual residual life expectancy strongly depended on colony demography instead of physiological age. While worker age affected queen longevity only slightly, exposing old workers to the conditions of colony founding increased their life spans by up to 50% relative to workers that had emerged shortly before colony set-up. Conclusions: The social environment strongly affected the tempo of aging and senescence in C. obscurior, highlighting the plasticity of life expectancy in social insects. Furthermore, colonies obtained the highest reproductive output when consisting of same-aged queens and workers independent of their physiological age. However, workers appeared to be able to adjust their behavior to the colony's needs and not to suffer from age-dependent restrictions