The emergence of the Internet of things and the widespread deployment of diverse
computing systems have led to the formation of heterogeneous multi-agent systems (MAS) …

Many systems or applications have been developed for distributed environments with the
goal of attaining multiple objectives in the face of environmental challenges such as high …

Task allocation is an important aspect of many multi-robot systems. The features and
complexity of multi-robot task allocation (MRTA) problems are dictated by the requirements …

Previous work on assigning tasks to robots has proposed extensive categorizations of
allocation of tasks with and without constraints. The main contribution of this paper is a …

We propose a decentralized belief propagation-based method, PD-LBP, for multi-agent task
allocation in open and dynamic grid and cloud environments where both the sets of agents …

The sports domain presents a number of significant computational challenges for artificial
intelligence (AI) and machine learning (ML). In this paper, we explore the techniques that …

Cooperative heterogeneous multirobot systems have attracted increasing attention in recent
years. They use multiple heterogeneous robots to execute complex tasks in a coordinated …

Effective deployment of multi-robot teams requires solving several interdependent problems
at varying levels of abstraction. Specifically, heterogeneous multi-robot systems must …

We propose a distributed approach to solve the multi-robot task allocation problem. This
problem consists of two distinct sets: robots and tasks. The objective is to assign tasks to …

Task allocation is a key issue in multi-agent systems, and finding the optimal strategy for task
allocation has been proved to be an NP-hard problem. Existing task allocation methods for …