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An important trend of real-time systems is to integrate applications with different criticality levels on a single multicore platform, enabling resource sharing among applications . However, the existing task allocation schemes suffer from the issue of ...

Facility location games have been studied extensively but most are about locating facilities given agents' profiles. However, in some real-life scenarios, the facility's location may be fixed already. When there are multiple facilities the strategic ...

In this paper, we present our focus on unraveling the intricacies of plan negotiation in human-robot collaborative navigation (HRCN) through a comprehensive exploration of human preferences over robot proposals in search tasks. Via online survey data, we ...

Task allocation is a key challenge in various fields due to increasing tasks and UAVs, leading to high computational costs. To tackle this, we employ swarm intelligence inspired by cooperative behaviours in lions, which is decentralised and adaptive. ...

Spatial crowdsourcing (SC) is a popular data collection paradigm for numerous applications. With the increment of tasks and workers in SC, heterogeneity becomes an unavoidable difficulty in task allocation. Existing researches only focus on the ...

We study how organizations use team selection and delegation of authority jointly to navigate uncertain environments. To do so, we model a managerial decision environment in which a manager both determines the skill heterogeneity of the workers and ...

Mobile Edge Computing (MEC) is considered as a promising technology to meet the high-quality service requirements of emerging applications in mobile intelligent terminals. It can effectively handle computation-intensive and latency-sensitive tasks ...

Cloud remains an active and dominant player in the field of information technology. Hence, to meet the rapidly growing requirement of computational processes and storage resources, the cloud provider deploys efficient data centres globally that ...

Task allocation in heterogeneous teams often requires reasoning about multi-dimensional agent traits (i.e., capabilities) and the demands placed on them. However, existing methods tend to ignore the fact that not all traits equally contribute to a task. ...

Multi-agent task allocation in physical environments with spatial and temporal constraints are hard problems relevant to many realistic applications. A task allocation algorithm based on Fisher market clearing (FMC_TA), which can be performed centrally ...

In this work, we design an Artificially Intelligent Task Allocator (AITA) that proposes a task allocation for multi-agent systems especially with humans. A key property of this allocation is that when an agent with imperfect knowledge (about their ...

Task allocation is an important problem for robot swarms to solve, allowing agents to reduce task completion time by performing tasks in a distributed fashion. Existing task allocation algorithms often assume prior knowledge of task location and demand ...

We consider agents having to schedule tasks within time slots they own on some resources. We focus on composite tasks that require multiple atomic tasks to be completed, potentially slotted into different private plans, and on disjunctive resources that ...

Efficiently allocating heterogeneous tasks to agents that arrive dynamically and have diverse skills is a central problem in multi-agent systems called online task allocation. In many cases, a single agent does not meet the skill levels required by a ...

A framework for spatial crowdsourcing task allocation based on centralized differential privacy is proposed for addressing the problem of worker’s location privacy leakage. Firstly, by combining two stages of differential privacy noise addition and ...

Disorganised and self-organised crowdsourcing activities that harness collective behaviours to achieve a specific level of performance and task completeness are not well understood. Such phenomena become indistinct when highly varied environments are ...

In the task allocation of mobile crowdsensing (MCS), importance is often attached to the quality of sensing data while the data timeliness is often neglected, which may lead to the slow response of the MCS platform for urgent tasks (such as fire, ...

Artificial Intelligence (AI) technology has been empowered to be a significant driven force within the edge context for powering up contemporary complex systems, such as smart critical infrastructure. Interconnectivity between physical and cyber spaces ...

The optimization of Task Allocation is an important and ongoing problem in the field of Internet-of-Things (IoT) networks. A sometimes overlooked aspect is the computational overhead of the employed optimization algorithms, which may require expensive ...

Multi-agent task allocation methods seek to distribute a set of tasks fairly amongst a set of agents. In real-world settings, such as fruit farms, human labourers undertake harvesting tasks, organised each day by farm manager(s) who assign workers to ...