The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform
Yaning Lin - One of the best experts on this subject based on the ideXlab platform.
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necessary sufficient conditions for Pareto Optimality in finite horizon mean field type stochastic differential game
Automatica, 2020Co-Authors: Yaning LinAbstract:Abstract This paper is concerned with necessary and sufficient conditions for the existence of Pareto solutions in finite horizon mean-field type stochastic cooperative differential game. Based on the equivalent characterization of Pareto Optimality, the problem is transformed into a set of constrained mean-field type stochastic optimal control problems with a special structure. Utilizing the mean-field type stochastic minimum principle, the necessary conditions are put forward. Under certain convex assumptions, it is shown that the necessary conditions are also sufficient ones. Next, the indefinite linear quadratic (LQ) case is studied. It is pointed out that the solvability of two related generalized differential Riccati equations (GDREs) provides a sufficient condition under which Pareto efficient strategies are equivalent to weighted sum optimal controls. In addition, all Pareto solutions are obtained based on the solutions of two generalized differential Lyapunov equations (GDLEs). At last, an example sheds light on the effectiveness of the theoretical results.
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Pareto Optimality in the infinite horizon cooperative difference game
IET Control Theory & Applications, 2020Co-Authors: Yaning LinAbstract:This study is concerned with the necessary and sufficient conditions for the existence of Pareto solutions in the infinite horizon cooperative difference game. Based on the assumption about the Lagrange multipliers, utilising the equivalent characterisation of the Pareto Optimality, the necessary conditions for the existence of the Pareto solutions are put forward. Furthermore, two conditions are presented to guarantee that zero does not belong to the Lagrange multiplier set. In addition, it is shown that the necessary conditions are also sufficient under certain convexity assumptions and a transversality condition. Next, the indefinite linear quadratic case is discussed. For a fixed initial state, under the condition of controllability, the necessary conditions are put forward. In addition, the necessary conditions, the convexity condition on the weighted sum cost functional as well as a transversality condition provide the sufficient conditions for a control to be Pareto optimal. For an arbitrary initial state, if the system is stabilisable, then the solvability of the related algebraic Riccati equation provides a sufficient condition under which all Pareto optimal strategies are obtained by the weighted sum minimisation method.
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necessary and sufficient conditions for Pareto Optimality of the stochastic systems in finite horizon
Automatica, 2018Co-Authors: Yaning Lin, Xiushan Jiang, Weihai ZhangAbstract:Abstract This paper is concerned with the necessary and sufficient conditions for the Pareto Optimality in the finite horizon stochastic cooperative differential game. Based on the necessary and sufficient characterization of the Pareto Optimality, the problem is transformed into a set of constrained stochastic optimal control problems with a special structure. Utilizing the stochastic Pontryagin minimum principle, the necessary conditions for the existence of the Pareto solutions are put forward. Under certain convex assumptions, it is shown that the necessary conditions are also sufficient ones. Next, we study the indefinite linear quadratic (LQ) case. It is pointed out that the solvability of the related generalized differential Riccati equation (GDRE) provides the sufficient condition under which all Pareto efficient strategies can be obtained by the weighted sum Optimality method. Two examples shed light on the effectiveness of theoretical results.
Tat-ming Lok - One of the best experts on this subject based on the ideXlab platform.
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Pareto Optimality for the Single-Stream Transmission in Multiuser Relay Networks
IEEE Transactions on Wireless Communications, 2017Co-Authors: Tat-ming LokAbstract:In this paper, we study Pareto Optimality for multiuser relay networks. We adopt single-stream transmission and amplify-and-forward relays. First, with fixed relay processing matrices and transmit and receive beamforming vectors, we study Pareto Optimality with respect to the power of the transmitters. Based on the signal-to-noise-plus-interference ratio (SINR) balancing analysis, we give a necessary and sufficient condition for a set of SINRs to be Pareto optimal. Second, we consider Pareto Optimality with respect to the relay processing matrices, where the power of the transmitters and the transmit and receive beamforming vectors is fixed. Taking advantage of multi-objective optimization analysis, we present a necessary and sufficient condition for a set of SINRs to be Pareto optimal. We also give a necessary condition to check whether Pareto Optimality is fulfilled. Finally, with fixed relay processing matrices, we study Pareto Optimality with respect to the transmit and receive beamforming vectors. Simulations show that our proposed algorithms outperform the compared schemes.
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Toward Pareto Optimality in Multiuser Relay Networks
IEEE Transactions on Vehicular Technology, 2017Co-Authors: Tat-ming LokAbstract:In this paper, we study the multiuser relay network in which each transmitter sends messages to its intended receiver with the help of a cluster of intelligent amplify-and-forward (AF) relays. We assume that each transmitter has the channel information of only the link to its corresponding receiver. With this assumption, we propose a joint optimization algorithm to achieve Pareto Optimality. Achieving Pareto Optimality of our relay network is more complicated than that of the one-hop interference channel since not only the beamforming vectors but also the processing matrices of the AF relays need to be optimized. With fixed relay processing matrices and minimum mean square error with successive interference cancelation (MMSE-SIC) receiver, we first find a sufficient condition for the transmission covariance to be Pareto optimal. Based on this sufficient condition, a transmit beamforming scheme is proposed. Then, by fixing transmit and receive beamforming vectors, we optimize the relay processing matrix and give a suboptimal algorithm to achieve the maximum sum rate and Pareto Optimality. Finally, by optimizing transmit beamforming vectors and relay processing matrices alternatively, we obtain the joint optimization algorithm, which can be guaranteed to be convergent. Simulation results show that our joint algorithm achieves much better performance than those schemes compared.
Paul Harrenstein - One of the best experts on this subject based on the ideXlab platform.
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a note on the mckelvey uncovered set and Pareto Optimality
Social Choice and Welfare, 2016Co-Authors: Felix Brandt, Christian Geist, Paul HarrensteinAbstract:We consider the notion of Pareto Optimality under the assumption that only the pairwise majority relation is known and show that the set of necessarily Pareto optimal alternatives coincides with the McKelvey uncovered set. As a consequence, the McKelvey uncovered set constitutes the coarsest Pareto optimal majoritarian social choice function. Moreover, every majority relation is induced by a preference profile in which the uncovered alternatives precisely coincide with the Pareto optimal ones. We furthermore discuss the structure of the McKelvey covering relation and the McKelvey uncovered set. Copyright Springer-Verlag Berlin Heidelberg 2016
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A note on the McKelvey uncovered set and Pareto Optimality
Social Choice and Welfare, 2015Co-Authors: Felix Brandt, Christian Geist, Paul HarrensteinAbstract:We consider the notion of Pareto Optimality under the assumption that only the pairwise majority relation is known and show that the set of necessarily Pareto optimal alternatives coincides with the McKelvey uncovered set. As a consequence, the McKelvey uncovered set constitutes the coarsest Pareto optimal majoritarian social choice function. Moreover, every majority relation is induced by a preference profile in which the uncovered alternatives precisely coincide with the Pareto optimal ones. We furthermore discuss the structure of the McKelvey covering relation and the McKelvey uncovered set.
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Pareto Optimality in coalition formation
Games and Economic Behavior, 2013Co-Authors: Haris Aziz, Felix Brandt, Paul HarrensteinAbstract:A minimal requirement on allocative efficiency in the social sciences is Pareto Optimality. In this paper, we identify a close structural connection between Pareto Optimality and perfection that has various algorithmic consequences for coalition formation. Based on this insight, we formulate the Preference Refinement Algorithm (PRA) which computes an individually rational and Pareto optimal outcome in hedonic coalition formation games. Our approach also leads to various results for specific classes of hedonic games. In particular, we show that computing and verifying Pareto optimal partitions in general hedonic games, anonymous games, three-cyclic games, room-roommate games and B-hedonic games is intractable while both problems are tractable for roommate games, W-hedonic games, and house allocation with existing tenants.
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Pareto Optimality in coalition formation
Algorithmic Game Theory, 2011Co-Authors: Haris Aziz, Felix Brandt, Paul HarrensteinAbstract:A minimal requirement on allocative efficiency in the social sciences is Pareto Optimality. In this paper, we identify a far-reaching structural connection between Pareto optimal and perfect partitions that has various algorithmic consequences for coalition formation. In particular, we show that computing and verifying Pareto optimal partitions in general hedonic games and B-hedonic games is intractable while both problems are tractable for roommate games and W-hedonic games. The latter two positive results are obtained by reductions to maximum weight matching and clique packing, respectively.
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SAGT - Pareto Optimality in coalition formation
Algorithmic Game Theory, 2011Co-Authors: Haris Aziz, Felix Brandt, Paul HarrensteinAbstract:A minimal requirement on allocative efficiency in the social sciences is Pareto Optimality. In this paper, we identify a far-reaching structural connection between Pareto optimal and perfect partitions that has various algorithmic consequences for coalition formation. In particular, we show that computing and verifying Pareto optimal partitions in general hedonic games and B-hedonic games is intractable while both problems are tractable for roommate games and W-hedonic games. The latter two positive results are obtained by reductions to maximum weight matching and clique packing, respectively.
Antoine Ferreira - One of the best experts on this subject based on the ideXlab platform.
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two dimensional robust magnetic resonance navigation of a ferromagnetic microrobot using Pareto Optimality
IEEE Transactions on Robotics, 2017Co-Authors: David Folio, Antoine FerreiraAbstract:This paper introduces a two-dimensional (2-D) autonomous navigation strategy of a 750- ${\mu \text{m}}$ steel microrobot along a complex fluidic vascular network inside the bore of a clinical 3.0-T magnetic resonance imaging (MRI) scanner. To ensure successful magnetic resonance navigation of a microrobot along consecutive channels, the design of autonomous navigation strategy is needed, taking into account the major MRI technological constraints and physiological perturbations, e.g., nonnegligible pulsatile flow, limitations on the magnetic gradient amplitude, MRI overheating, and susceptibility artifacts uncertainties. An optimal navigation planning framework based on Pareto Optimality is proposed in order to deal with this multiple-objective problem. Based on these optimal conditions, a dedicated control architecture has been implemented in an interventional medical platform for real-time propulsion, control, and imaging experiments. The reported experiments suggest that the likelihood of controlling autonomously untethered 750- ${\mu \text{m}}$ magnetic microrobots is rendered possible in a complex 2-D centimeter-sized vascular phantom. The magnetic microrobot traveled intricate paths at a mean velocity of about 4 $\text{mms}^{-1}$ with average tracking errors below 800 ${\mu \text{m}}$ with limited magnetic gradients $\pm \text{15}\ \text{mTm}^{-1}$ , which is compatible with clinical MRI scanners. The experiments demonstrate that it is effectively possible to autonomously guide a magnetic microrobot using a conventional MRI scanner with only a software upgrade.
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2D Robust Magnetic Resonance Navigation of a Ferromagnetic Microrobot using Pareto Optimality
IEEE Transactions on Robotics, 2017Co-Authors: David Folio, Antoine FerreiraAbstract:This paper introduces a two-dimensional autonomous navigation strategy of a 750 µm steel microrobot along a complex fluidic vascular network inside the bore of a clinical 3.0 T magnetic resonance imaging (MRI) scanner. To ensure successful magnetic resonance navigation (MRN) of a micro-robot along consecutive channels, the design of autonoumous navigation strategy is needed taking into account the major MRI technological constraints and physiological perturbations, e.g. non-negligible pulsatile flow, limitations on the magnetic gradient amplitude, MRI overheating, susceptibility artifacts uncertainties , and so on. An optimal navigation planning framework based on Pareto Optimality is proposed in order to deal with this multiple-objective problem. Based on these optimal conditions, a dedicated control architecture has been implemented in an interventional medical platform for real-time propulsion, control and imaging experiments. The reported experiments suggest that the likelihood of controlling autonomously untethered 750 µm magnetic microrobots is rendered possible in a complex two-dimensional centimeter-sized vascular phantom. The magnetic microrobot traveled intricate paths at a mean velocity of about 4 mm s −1 with average tracking errors below 800 µm with limited magnetic gradients ±15 mT m −1 compatible with clinical MRI scanners. The experiments demonstrate that it is effectively possible to autonomously guide a magnetic microrobot using a conventional MRI scanner with only a software upgrade.
Felix Brandt - One of the best experts on this subject based on the ideXlab platform.
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a note on the mckelvey uncovered set and Pareto Optimality
Social Choice and Welfare, 2016Co-Authors: Felix Brandt, Christian Geist, Paul HarrensteinAbstract:We consider the notion of Pareto Optimality under the assumption that only the pairwise majority relation is known and show that the set of necessarily Pareto optimal alternatives coincides with the McKelvey uncovered set. As a consequence, the McKelvey uncovered set constitutes the coarsest Pareto optimal majoritarian social choice function. Moreover, every majority relation is induced by a preference profile in which the uncovered alternatives precisely coincide with the Pareto optimal ones. We furthermore discuss the structure of the McKelvey covering relation and the McKelvey uncovered set. Copyright Springer-Verlag Berlin Heidelberg 2016
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A note on the McKelvey uncovered set and Pareto Optimality
Social Choice and Welfare, 2015Co-Authors: Felix Brandt, Christian Geist, Paul HarrensteinAbstract:We consider the notion of Pareto Optimality under the assumption that only the pairwise majority relation is known and show that the set of necessarily Pareto optimal alternatives coincides with the McKelvey uncovered set. As a consequence, the McKelvey uncovered set constitutes the coarsest Pareto optimal majoritarian social choice function. Moreover, every majority relation is induced by a preference profile in which the uncovered alternatives precisely coincide with the Pareto optimal ones. We furthermore discuss the structure of the McKelvey covering relation and the McKelvey uncovered set.
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Pareto Optimality in coalition formation
Games and Economic Behavior, 2013Co-Authors: Haris Aziz, Felix Brandt, Paul HarrensteinAbstract:A minimal requirement on allocative efficiency in the social sciences is Pareto Optimality. In this paper, we identify a close structural connection between Pareto Optimality and perfection that has various algorithmic consequences for coalition formation. Based on this insight, we formulate the Preference Refinement Algorithm (PRA) which computes an individually rational and Pareto optimal outcome in hedonic coalition formation games. Our approach also leads to various results for specific classes of hedonic games. In particular, we show that computing and verifying Pareto optimal partitions in general hedonic games, anonymous games, three-cyclic games, room-roommate games and B-hedonic games is intractable while both problems are tractable for roommate games, W-hedonic games, and house allocation with existing tenants.
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Pareto Optimality in coalition formation
Algorithmic Game Theory, 2011Co-Authors: Haris Aziz, Felix Brandt, Paul HarrensteinAbstract:A minimal requirement on allocative efficiency in the social sciences is Pareto Optimality. In this paper, we identify a far-reaching structural connection between Pareto optimal and perfect partitions that has various algorithmic consequences for coalition formation. In particular, we show that computing and verifying Pareto optimal partitions in general hedonic games and B-hedonic games is intractable while both problems are tractable for roommate games and W-hedonic games. The latter two positive results are obtained by reductions to maximum weight matching and clique packing, respectively.
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SAGT - Pareto Optimality in coalition formation
Algorithmic Game Theory, 2011Co-Authors: Haris Aziz, Felix Brandt, Paul HarrensteinAbstract:A minimal requirement on allocative efficiency in the social sciences is Pareto Optimality. In this paper, we identify a far-reaching structural connection between Pareto optimal and perfect partitions that has various algorithmic consequences for coalition formation. In particular, we show that computing and verifying Pareto optimal partitions in general hedonic games and B-hedonic games is intractable while both problems are tractable for roommate games and W-hedonic games. The latter two positive results are obtained by reductions to maximum weight matching and clique packing, respectively.
