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We present an overview of the Task Coordination (TC) problem in multiagent systems and discuss the specific elements that are required to develop a solution to this problem. Task coordination refers to a twofold problem where an exogenously imposed ...

We call for attention to climate change research as a domain of application for multiagent technologies. The multiagent nature of climate change challenges and successful application of multiagent methods in decentralized power grid systems, market ...

Evolutionary optimization is a generic population-based metaheuristic that can be adapted to solve a wide variety of optimization problems and has proven very effective for combinatorial optimization problems. However, the potential of this ...

People who observe a multi-agent team can often provide valuable information to the agents based on their superior cognitive abilities to interpret sequences of observations and assess the overall situation. The knowledge they possess is often difficult ...

Distributed Constraint Optimization Problems (DCOPs) can be used to model a number of multi-agent coordination problems. The conventional DCOP model assumes that the subproblem that each agent is responsible for (i.e. the mapping of nodes in the ...

Generalized Distributive Law (GDL) based message passing algorithms, such as Max-Sum and Bounded Max Sum, are often used to solve distributed constraint optimization problems in cooperative multi-agent systems (MAS). However, scalability becomes a ...

We consider a market where a seller sells multiple units of a commodity in a social network. Each node/buyer in the social network can only directly communicate with her neighbours, i.e. the seller can only sell the commodity to her neighbours if she ...

Over the past few years, Domestic Heating Automation Systems (DHASs) that optimize the domestic space heating control process with minimum user input, utilizing appropriate occupancy prediction technology, have emerged as commercial products (e.g., the ...

Collaboration is essential for effective performance by groups of robots in disaster response settings. Here we are particularly interested in heterogeneous robots that collaborate in complex scenarios with incomplete, dynamically changing information. ...

We consider settings where owners of electric vehicles (EVs) participate in a market mechanism to charge their vehicles. Existing work on such mechanisms has typically assumed that participants are fully rational and can report their preferences ...

We study a general task allocation problem, involving multiple agents that collaboratively accomplish tasks and where agents may fail to successfully complete the tasks assigned to them (known as execution uncertainty). The goal is to choose an ...

Many aspects of the design of efficient crowdsourcing processes, such as defining worker's bonuses, fair prices and time limits of the tasks, involve knowledge of the likely duration of the task at hand. In this work we introduce a new time-sensitive ...

Social media has led to the democratisation of opinion sharing. A wealth of information about public opinions, current events, and authors' insights into specific topics can be gained by understanding the text written by users. However, there is a wide ...

Improving the energy efficiency of domestic heating systems can lead to a major reduction in energy consumption and the corresponding CO₂ emissions. To this end, intelligent domestic heating agents (IDHAs) aim to operate domestic heating systems more ...

This paper proposes a novel disaster management system called HAC-ER that addresses some of the challenges faced by emergency responders by enabling humans and agents, using state-of-the-art algorithms, to collaboratively plan and carry out tasks in ...

Environmental monitoring is important, as it allows authorities to understand the impact of potentially harmful environmental phenomena, such as air pollution, noise or temperature, on public health. To achieve this effectively, participatory sensing is ...

Recently, many algorithms have been developed for autonomous agents to manage home energy use on behalf of their human owners. By so doing, it is expected that agents will be more efficient at, for example, choosing the best energy tariff to switch to ...

Current electricity tariffs do not reflect the real costs that a customer incurs to a supplier, as units are charged at the same rate, regardless of the consumption pattern. In this paper, we propose a prediction-of-use tariff that better reflects these ...

Crowdsourcing is a multi-agent task allocation paradigm that involves up to millions of workers, of varying reliability and availability, performing large numbers of micro-tasks. A key challenge is to crowdsource, at minimal cost and with predictable ...