This paper addresses the Multi-Robot Patrolling Problem, where agents must coordinate
their actions while continuously deciding which place to move next after clearing their …

Patrolling indoor infrastructures with a team of cooperative mobile robots is a challenging
task, which requires effective multi-agent coordination. Deterministic patrol circuits for …

In this paper the problem of patrolling an environment with a dynamic team of robots is
targeted. Lately, the interest of the research community has been focused in the …

Experiments with teams of mobile robots in the physical world often represent a challenging
task due to the complexity involved. One has to make sure that the robot hardware …

For over a decade, the multi-agent patrolling task has received attention from the multi-agent
community. A range of algorithms based on reactive and cognitive architectures has been …

Performing a patrolling mission with multiple mobile robots is a challenging task that
requires effective coordination between agents. While predefined patrol circuits may lead to …

We propose a learning and negotiation method to enhance divisional cooperation and
demonstrate its flexibility for adapting to environmental changes in the context of the multi …

We propose a method of autonomous learning of target decision strategies for coordination
in the continuous cleaning domain. With ongoing advances in computer and sensor …

Abstract Multi-Agent Patrolling Problems consist in moving agents throughout a graph in
order to optimize a collective performance metric. Some strategies from the literature tackle …

We propose a conceptually simple new decentralised and non-communicating strategy for
the multi-agent patrolling based on the LSTM architecture. The recurrent neural networks …