A Markov Model for Multiagent Patrolling in Continuous Time

Marier, Jean-Samuel; Besse, Camille; Chaib-draa, Brahim

doi:10.1007/978-3-642-10684-2_72

Cited by 7 publications

(4 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…More recent works are those by Almeida [1], Chevaleyre [3], [4], Santana [16], Lauri [7], [9], Marier [13] and Poulet [14].…”

Section: Related Workmentioning

confidence: 98%

See 1 more Smart Citation

Hybrid ACO/EA algorithms applied to the multi-agent patrolling problem

Lauri¹,

Koukam²

2014

2014 IEEE Congress on Evolutionary Computation (CEC)

View full text Add to dashboard Cite

Patrolling an environment consists in visiting as frequently as possible its most relevant areas in order to supervise, control or protect it. This task is commonly performed by a team of agents that need to coordinate their actions for achieving optimal performance. We address here the problem of multiagent patrolling in known environments where agents may move at different speeds and visit priorities on some areas may be specified. Two classes of patrolling strategies are studied: the single-cycle strategies and the partition-based strategies. Several single-core and multi-core variants of a template state-of-theart hybrid algorithm are proposed for generating partitionbased strategies. These are experimentally compared with a state-of-the-art heuristic-based algorithm generating single-cycle strategies. Experimental results show that: the heuristic-based algorithm only generates efficient strategies when agents move at the same speeds and no visit priorities have been defined; all single-core variants are equivalent; multi-core hybrid algorithms may improve overall quality or reduce variance of the solutions obtained by single-core algorithms.

show abstract

“…More recent works are those by Almeida [1], Chevaleyre [3], [4], Santana [16], Lauri [7], [9], Marier [13] and Poulet [14].…”

Section: Related Workmentioning

confidence: 98%

“…Marier et al [13] define the multi-agent patrolling problem as a Generalized Semi-Markov Decision Process (GSMDP). This mathematical model can handle continuous time and uncertainties in the execution of a patrol.…”

Section: Related Workmentioning

confidence: 99%

Hybrid ACO/EA algorithms applied to the multi-agent patrolling problem

Lauri¹,

Koukam²

2014

2014 IEEE Congress on Evolutionary Computation (CEC)

View full text Add to dashboard Cite

show abstract

“…These are denoted herein as Alternative strategies. In the literature, there can be found solutions based on task allocation [7], Markov decision processes [8] and others. For a more thorough survey of multirobot patrolling architectures, one should refer to [1].…”

Section: A Related Workmentioning

confidence: 99%

Decision methods for distributed multi-robot patrol

Portugal

Rocha

2012

2012 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)

View full text Add to dashboard Cite

In the Multi-Robot Patrolling Problem, agents have to continuously decide which place to move next, after clearing their current location. This article proposes a distributed solution to the problem based on Bayesian decision. The system is modeled according to its current state, thus automating the local decisionmaking process in order to effectively patrol an area.Two strategies are presented and compared. In the first one, robots are self-interested and aim to maximize their local gain. The second strategy is more complex, taking into account gains as well as the distribution of agents in the space to reduce interference and foster scalability. In order to validate the proposed solution, realistic simulations, comparing with five state-of-the-art approaches, as well as experiments with physical multi-robot systems were conducted.

show abstract

“…Finding effective patrolling strategies for moving sensors around the environment received a remarkable attention in literature [1], [2]. Originally the problem has been investigated in non-adversarial scenarios [1], [3]. Emerging approaches focus on adversarial scenarios, where the interaction with a rational intruder agent is explicitly taken into account and the patrolling strategy is computed exploiting game theoretical techniques [2], [4], [5].…”

Section: Introductionmentioning

confidence: 99%

A Game-Theoretical Model Applied to an Active Patrolling Camera

Basilico

Rossignoli

Gatti

et al. 2010

2010 International Conference on Emerging Security Technologies

View full text Add to dashboard Cite

In patrolling, an agent perceives portions of an environment to detect the presence of an intruder. Usually, the agent cannot perceive the whole environment at once, but can change over time the observed portion. Finding an optimal patrolling strategy that minimizes the possibility of intrusions constitutes one of the main scientific problems in this field. Game theoretical models have been recently employed to compute effective patrolling strategies that explicitly consider the presence of a rational intruder. In this paper, we present a general game theoretical framework for computing patrolling strategies for different kinds of patrollers. In particular, we study the case of an active patrolling camera.

show abstract

A Markov Model for Multiagent Patrolling in Continuous Time

Cited by 7 publications

References 1 publication

Hybrid ACO/EA algorithms applied to the multi-agent patrolling problem

Hybrid ACO/EA algorithms applied to the multi-agent patrolling problem

Decision methods for distributed multi-robot patrol

A Game-Theoretical Model Applied to an Active Patrolling Camera

Contact Info

Product

Resources

About