Task Allocation in Ant Colonies

Cornejo, Alejandro; Dornhaus, Anna; Lynch, Nancy; Nagpal, Radhika

doi:10.1007/978-3-662-45174-8_4

Cited by 33 publications

(24 citation statements)

References 37 publications

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“…We discuss what the consequences of specific individual-level behavioral rules are for the allocation of these individuals to tasks, and how this may result in group-level function, for example with regard to group division of labor, robustness, and efficiency. Drawing on models of division of labor that have been discovered or proposed for social insect colonies, we review strategies for task allocation, or the behavioral rules that regulate which tasks workers engage in (Brutschy et al 2014;Cornejo et al 2014). We discuss their advantages and limitations as well as those situations for which they may be optimal; we then discuss how these task allocation strategies may also generate differences in activity level among individuals, and why some individuals may appear entirely inactive.…”

Section: Introductionmentioning

confidence: 99%

When doing nothing is something. How task allocation strategies compromise between flexibility, efficiency, and inactive agents

Charbonneau

Dornhaus

2015

J Bioecon

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We expect that human organizations and cooperative animal groups should be optimized for collective performance. This often involves the allocation of different individuals to different tasks. Social insect colonies are a prime example of cooperative animal groups that display sophisticated mechanisms of task allocation. Here we discuss which task allocation strategies may be adapted to which environmental and social conditions. Effective and robust task allocation is a hard problem, and in many biological and engineered complex systems is solved in a decentralized manner: human organizations may benefit from insights into what makes decentralized strategies of group organization effective. In addition, we often find considerable variation among individuals in how much work they appear to contribute, despite the fact that individual selfishness in social insects is low and optimization occurs largely at the group level. We review possible explanations for uneven workloads among workers, including limitations on individual information collection or constraints of task allocation efficiency, such as when there is a mismatch between the frequency of fluctuations in demand for work and the speed at which workers can be reallocated. These processes are likely to apply to any system in which worker agents are allocated to tasks with fluctuating demand, and should therefore be instructive to understanding optimal task allocation and inactive workers in any distributed system. Some of these processes imply that a certain proportion of inactive workers can be an adaptive strategy for collective organization.

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Section: Introductionmentioning

confidence: 99%

When doing nothing is something. How task allocation strategies compromise between flexibility, efficiency, and inactive agents

Charbonneau

Dornhaus

2015

J Bioecon

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“…Indeed, the coordination of distributed and heterogeneous energy resources for the provision of FCR reserves consist of a complex task, in which the aggregator has the responsibility of coordinating a large amount of energy resources, as specified in [34]. Therefore, the task allocation algorithm is formulated as a swarm intelligence model as defined by Cornejo et al [35], where an auction-based mechanism is employed to allocate the tasks to the energy resources [33]. In fact, auctions are multidisciplinary methods employed to solve complex task and resource management problems [36].…”

Section: Related Workmentioning

confidence: 99%

Task Allocation Algorithm for Energy Resources Providing Frequency Containment Reserves

Giovanelli

Kilkki

Sierla

et al. 2019

IEEE Trans. Ind. Inf.

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The uncertainty caused by the variability in renewable energy production requires the engagement of consumer-side energy production and consumption to provide sufficient flexibility and reliability for the power grid. This study presents an algorithm for allocating tasks to distributed energy resources allowing consumers to provide flexibility for frequency containment reserves. The task allocation algorithm aims at supporting the plug and play of energy resources, and it avoids the need for hard real-time messages during the coordination of the resources. The algorithm combines a novel control strategy with an information and communication technology architecture. The main decision logic of the algorithm is defined together with the distributed control logic. A prototype implementation of the overall system for frequency control is used to evaluate the performance of the algorithm. The simulation results show that the algorithm achieves the specified objectives, and has advantages compared to the state of the art solution.

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“…As a result, approaches that mimic some of their characteristics and mechanisms (e.g., stigmergy) have been exhaustively applied in robotics (e.g., Refs. ), task allocation or optimization and can also be adopted to implement autonomous systems. The following sections will present how some of these concepts and autonomous system paradigms have been applied to satellite missions and what are the necessary ingredients to ultimately achieve fully autonomous DSS.…”

Section: Autonomymentioning

confidence: 99%

Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects

Araguz

Bou-Balust

Alarcón

2018

Systems Engineering

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While monolithic satellite missions still pose significant advantages in terms of accuracy and operations, novel distributed architectures are promising improved flexibility, responsiveness and adaptability to structural and functional changes. Large satellite swarms, opportunistic satellite networks or heterogeneous constellations hybridizing small-spacecraft nodes with high-performance satellites are becoming feasible and advantageous alternatives requiring the adoption of new operation paradigms that enhance their autonomy. While autonomy is a notion that is gaining acceptance in monolithic satellite missions, it can also be deemed an integral characteristic in Distributed Satellite Systems. In this context, this paper focuses on the motivations for system-level autonomy in DSS and justifies its need as an enabler of system qualities.Autonomy is also presented as a necessary feature to bring new distributed Earth observation functions (which require coordination and collaboration mechanisms) and to allow for novel structural functions (e.g. opportunistic coalitions, exchange of resources or in-orbit data services).Mission Planning and Scheduling frameworks (MPS) are then presented as a key component to * Corresponding author. E-mail addresses: {carles.araguz, elisenda.bou, eduard.alarcon}@upc.edu 1 implement autonomous operations in satellite missions. An exhaustive knowledge classification explores the design aspects of MPS for DSS, and conceptually groups them into: components and organizational paradigms; problem modeling and representation; optimization techniques and metaheuristics; execution and runtime characteristics; and the notions of tasks, resources and constraints. This paper concludes by proposing future strands of work devoted to study the tradeoffs of autonomy in large-scale, highly dynamic and heterogeneous networks through frameworks that consider some of the limitations of small spacecraft technologies.

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Task Allocation in Ant Colonies

Cited by 33 publications

References 37 publications

When doing nothing is something. How task allocation strategies compromise between flexibility, efficiency, and inactive agents

When doing nothing is something. How task allocation strategies compromise between flexibility, efficiency, and inactive agents

Task Allocation Algorithm for Energy Resources Providing Frequency Containment Reserves

Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects

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