On the value of information in a differential pursuit-evasion game

Becerra, Israel; Macias, Vladimir; Murrieta-Cid, Rafael

doi:10.1109/icra.2015.7139862

Cited by 8 publications

(6 citation statements)

References 15 publications

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“…Pursuit problem [1][2][3][4][5][6][7][8][9][10][11][12][13] is one of the hot spots in the field of artificial intelligence, and it is also a typical problem to study the cooperation and confrontation of multiple robots. Pursuit problem originates from the predatory behavior of the animal kingdom, such as coyotes to hunt preys.…”

Section: Introductionmentioning

confidence: 99%

“…The literature [16] firstly proposes a pursuit method based on differential game in 1965, but this method is mainly suitable for one to one pursuit, but not suitable for many to one or many to many problem, and solving optimal pursuit strategy is difficult, as well as Nash optimal equilibrium solution may not exist. The literatures [3][4][5][6]17] propose the pursuit-evasion games that the speed of the pursuers is greater than the evaders. Therefore, the capture of the evaders can be guaranteed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Research on Synergy Pursuit Strategy of Multiple Underwater Robots

Jia

et al. 2019

J Intell Robot Syst

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This paper presents a synergy pursuit strategy that multiple underwater robots pursue a single moving target based on finite state machine. The processes of the pursuit are defined as seven different states, and to implement each state, the corresponding strategies are designed. As the strategy for each state is implemented by a corresponding formation control, a synergy control law is also designed for multiple underwater robots. In the design of the pursuit strategy, the definition of encirclement is put forward for the underwater robots. Furthermore, the proof that a point is encircled by other points on the plane is given. To solve the problem of the concealment in the tracking and the pursuit, a semicircular pursuit strategy and a circular pursuit strategy are also proposed. Finally, based on this pursuit strategy, the simulation of whole process is carried out with the MOOS(Mission Oriented Operating Suite) platform, and the effectiveness of the semicircular and circular pursuit strategy are verified by lake experiment with practical robots. The results of simulation and lake experiment prove that this pursuit strategy can realize synergy tracking and pursuit for a single moving target under the given conditions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on Synergy Pursuit Strategy of Multiple Underwater Robots

Jia

et al. 2019

J Intell Robot Syst

View full text Add to dashboard Cite

show abstract

“…In 1965, the literature [3] firstly proposes a pursuit method based on differential games, but this method is mainly suitable for oneto-one pursuit, but not for many-to-one or many-to-many pursuit problem. According to the pursuit game proposed in literatures [4][5], the speed of the pursuer is greater than that of the escapee. As long as the pursuer adopts the corresponding pursuit strategy, the escapee must be captured.…”

Section: Introductionmentioning

confidence: 99%

A Novel Cooperative Pursuit Strategy in Multiple Underwater robots

Jia

Feng

et al. 2019

OCEANS 2019 - Marseille

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A novel cooperative pursuit strategy for multiple underwater robots is proposed in this paper. In this pursuit strategy, the pursuit-evasion game is studied in two stages. In the first stages, when the target keeps the static state, the rapidlyexploring random tree (RRT) search algorithm is used to realize the real-time path replanning for multiple underwater robots, so as to avoid the target detection range and reach the desired precapture position. Therefore, the concealed problem of encircling the static target is solved. In the second stages, when multiple underwater robots enter into the target detection range, the target will start to escape. In order to solve the problem of capturing a moving target, the cooperative control law for multiple underwater robots is proposed. A circular formation is formed to pursue the target using the cooperative control law so that the capture error can meet a certain performance indexes. Finally, the simulation results show the effectiveness and feasibility of the proposed cooperative pursuit strategy.

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“…A number of articles [54,61,[63][64][65]100] investigated pursuit-evasion games with slow evaders, where the capture of the evader is always guaranteed. However, in real-world applications, evaders may run with speed similar to or higher than the speed of pursuers.…”

Section: Motivationmentioning

confidence: 99%

“…A variety of pursuit-evasion games have been studied in different contexts [52][53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70][71].…”

Section: The Pursuit-evasion Gamementioning

confidence: 99%

On Multi-Agent Reinforcement Learning in Matrix, Stochastic and Differential Games

Awheda¹

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In this thesis, we investigate reinforcement learning algorithms on matrix, stochastic, and differential games. In matrix and stochastic games, the states and actions are represented in continuous domains. We propose two decentralized multi-agent reinforcement learning algorithms to solve the problem of learning in matrix and stochastic games when the learning agent has only minimum knowledge about the underlying game and the other learning agents. The proposed algorithms are the constant learning rate-based exponential moving average Q-learning (CLR-EMAQL) algorithm, and the exponential moving average Q-learning (EMAQL) algorithm. We mathematically show that the proposed CLR-EMAQL algorithm converges to Nash equilibrium in games with pure Nash equilibrium. We introduce the concept of Win-or-Learn-Slow (WoLS) mechanism for the proposed EMAQL algorithm so that the proposed algorithm learns fast when it is winning, and learns cautiously when it is losing. We also provide a theoretical proof of convergence to Nash equilibrium for the proposed EMAQL algorithm in games with pure Nash equilibrium. In games with mixed Nash equilibrium, our mathematical analysis shows that the proposed EMAQL algorithm converges to an equilibrium. Although our mathematical analysis does not explicitly show that the proposed EMAQL algorithm converges to Nash equilibrium, our simulation results indicate that the proposed EMAQL algorithm does converge to Nash equilibrium. Our simulation iii I would like to express my deepest gratitude to my advisor, Professor Howard M.

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On the value of information in a differential pursuit-evasion game

Cited by 8 publications

References 15 publications

Research on Synergy Pursuit Strategy of Multiple Underwater Robots

Research on Synergy Pursuit Strategy of Multiple Underwater Robots

A Novel Cooperative Pursuit Strategy in Multiple Underwater robots

On Multi-Agent Reinforcement Learning in Matrix, Stochastic and Differential Games

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