The Experts below are selected from a list of 141 Experts worldwide ranked by ideXlab platform
Koen V Hindriks - One of the best experts on this subject based on the ideXlab platform.
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a semantic framework for socially adaptive agents towards Strong Norm compliance
Adaptive Agents and Multi-Agents Systems, 2015Co-Authors: Birna M Van Riemsdijk, Louise A Dennis, Michael Fisher, Koen V HindriksAbstract:We address the question of how an agent can adapt its behavior to comply with newly adopted Norms. This is particularly relevant in the case of open systems where agents may enter and leave Norm-governed social contexts not known at design time. This requires Norms to be explicitly and separately stated and presented to an agent as rules to which it then can try to adapt its behavior.We propose a formal semantic framework that specifies an execution mechanism for such socially adaptive agents. This framework is based on expressing Norms using Linear Temporal Logic. The formality of the framework allows us to rigorously study its Norm compliance properties. A weak form of Norm compliance allows agents to abort execution in order to prevent Norm violation. In this paper we investigate a Stronger notion of Norm compliance that is evaluated over infinite traces. We show that it is not possible for all agents to be Strongly compliant with any arbitrary set of Norms. We then investigate situations when Strong Norm compliance can be guaranteed.
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AAMAS - A Semantic Framework for Socially Adaptive Agents: Towards Strong Norm compliance
2015Co-Authors: M. Birna Van Riemsdijk, Louise A Dennis, Michael Fisher, Koen V HindriksAbstract:We address the question of how an agent can adapt its behavior to comply with newly adopted Norms. This is particularly relevant in the case of open systems where agents may enter and leave Norm-governed social contexts not known at design time. This requires Norms to be explicitly and separately stated and presented to an agent as rules to which it then can try to adapt its behavior. We propose a formal semantic framework that specifies an execution mechanism for such socially adaptive agents. This framework is based on expressing Norms using Linear Temporal Logic. The formality of the framework allows us to rigorously study its Norm compliance properties. A weak form of Norm compliance allows agents to abort execution in order to prevent Norm violation. In this paper we investigate a Stronger notion of Norm compliance that is evaluated over infinite traces. We show that it is not possible for all agents to be Strongly compliant with any arbitrary set of Norms. We then investigate situations when Strong Norm compliance can be guaranteed.
V. V. Smagin - One of the best experts on this subject based on the ideXlab platform.
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Strong-Norm Error Estimates for the Projective-Difference Method for Parabolic Equations with Modified Crank--Nicolson Scheme
Mathematical Notes, 2003Co-Authors: V. V. SmaginAbstract:A parabolic problem in a separable Hilbert space is solved approximately by the projective-difference method. The problem is discretized with respect to space by the Galerkin method and with respect to time by the modified Cranck--Nicolson scheme. In this paper, we establish efficient (in time and space) Strong-Norm error estimates for approximate solutions. These estimates allow us to obtain the rate of convergence with respect to time of the error to zero up to the second order. In addition, the error estimates take into account the approximation properties of projective subspaces, which is illustrated for subspaces of finite element type.
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Strong-Norm error estimates for the projective-difference method for approximately solving abstract parabolic equations
Mathematical Notes, 1997Co-Authors: V. V. SmaginAbstract:Solutions continuously differentiable with respect to time of parabolic equations in Hilbert space are obtained by the projective-difference method approximately. The discretization of the problem is carried out in the spatial variables using Galerkin's method, and in the time variable using Euler's implicit method. Strong-Norm error estimates for approximate solutions are obtained. These estimates not only allow one to establish the convergence of the approximate solutions to the exact ones but also yield numerical characteristics of the rates of convergence. In particular, order-sharp error estimates for finite element subspaces are obtained.
Diego Armando Ruedagomez - One of the best experts on this subject based on the ideXlab platform.
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study of a chemo repulsion model with quadratic production part i analysis of the continuous problem and time discrete numerical schemes
Computers & Mathematics With Applications, 2020Co-Authors: Francisco Guillengonzalez, Maria Angeles Rodriguezbellido, Diego Armando RuedagomezAbstract:Abstract We consider a chemo-repulsion model with quadratic production in a bounded domain. Firstly, we obtain global in time weak solutions, and give a regularity criterion (which is satisfied for 1 D and 2 D domains) to deduce uniqueness and global regularity. After, we study two cell-conservative and unconditionally energy-stable first-order time schemes: a (nonlinear and positive) Backward Euler scheme and a linearized coupled version, proving solvability, convergence towards weak solutions and error estimates. In particular, the linear scheme does not preserve positivity and the uniqueness of the nonlinear scheme is proved assuming small time step with respect to a Strong Norm of the discrete solution. This hypothesis is reduced to small time step in n D domains ( n ≤ 2 ) where global in time Strong estimates are proved. Finally, we show the behavior of the schemes through some numerical simulations.
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study of a chemo repulsion model with quadratic production part i analysis of the continuous problem and time discrete numerical schemes
arXiv: Numerical Analysis, 2018Co-Authors: Francisco Guillengonzalez, Maria Angeles Rodriguezbellido, Diego Armando RuedagomezAbstract:We consider a chemo-repulsion model with quadratic production in bounded domains, which is a nonlinear parabolic system for two variables; the cell density and the chemical concentration. We present two mass-conservative and unconditional energy-stable first order time schemes: the (nonlinear) Backward Euler scheme and a linearized coupled version. We also analyze positivity, solvability, convergence towards weak solutions and error estimates of these schemes. In particular, uniqueness of the nonlinear scheme is proved assuming small time step with respect to a Strong Norm of the scheme. This hypothesis is simplified in $2D$ domains where a global in time Strong estimate is proved. Finally, we show the behavior of the schemes through some numerical simulations.
Gurubachan. S. Munde - One of the best experts on this subject based on the ideXlab platform.
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Stability of a multi-input, multi-output adaptive iterative learning control system
1997 European Control Conference (ECC), 1997Co-Authors: David H. Owens, Gurubachan. S. MundeAbstract:This paper provides convergence/stability criteria for universal adaptive high-gain iterative learning control systems based on the use of the current trial feedback for a class of linear, multi-input multi-output (MIMO) state space systems. Weak and Strong (Norm) convergence of the tracking error sequence {e k } k≥0 to zero in Lm 2 (0, T) is analysed. This perfect tracking is also achieved with the proposed gain-update laws, with convergence of the adaptive control K k to a limit gain K ∞ guaranteed.
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Universal adaptive iterative learning control
Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171), 1Co-Authors: David H. Owens, Gurubachan. S. MundeAbstract:This paper provides convergence/stability criteria for universal adaptive high-gain iterative learning control systems based on the use of the current trial feedback for a class of linear MIMO state space systems. Weak and Strong (Norm) convergence of the tracking error sequences {e/sub k/}/sub k/spl ges/0/ to zero in L/sub 2//sup m/(0,T) is analysed. This perfect tracking is is also achieved with convergence of the adaptive control K/sub k/ to a limit gain K/sub /spl infin// guaranteed in the proposed gain-update laws.
Michael Fisher - One of the best experts on this subject based on the ideXlab platform.
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a semantic framework for socially adaptive agents towards Strong Norm compliance
Adaptive Agents and Multi-Agents Systems, 2015Co-Authors: Birna M Van Riemsdijk, Louise A Dennis, Michael Fisher, Koen V HindriksAbstract:We address the question of how an agent can adapt its behavior to comply with newly adopted Norms. This is particularly relevant in the case of open systems where agents may enter and leave Norm-governed social contexts not known at design time. This requires Norms to be explicitly and separately stated and presented to an agent as rules to which it then can try to adapt its behavior.We propose a formal semantic framework that specifies an execution mechanism for such socially adaptive agents. This framework is based on expressing Norms using Linear Temporal Logic. The formality of the framework allows us to rigorously study its Norm compliance properties. A weak form of Norm compliance allows agents to abort execution in order to prevent Norm violation. In this paper we investigate a Stronger notion of Norm compliance that is evaluated over infinite traces. We show that it is not possible for all agents to be Strongly compliant with any arbitrary set of Norms. We then investigate situations when Strong Norm compliance can be guaranteed.
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AAMAS - A Semantic Framework for Socially Adaptive Agents: Towards Strong Norm compliance
2015Co-Authors: M. Birna Van Riemsdijk, Louise A Dennis, Michael Fisher, Koen V HindriksAbstract:We address the question of how an agent can adapt its behavior to comply with newly adopted Norms. This is particularly relevant in the case of open systems where agents may enter and leave Norm-governed social contexts not known at design time. This requires Norms to be explicitly and separately stated and presented to an agent as rules to which it then can try to adapt its behavior. We propose a formal semantic framework that specifies an execution mechanism for such socially adaptive agents. This framework is based on expressing Norms using Linear Temporal Logic. The formality of the framework allows us to rigorously study its Norm compliance properties. A weak form of Norm compliance allows agents to abort execution in order to prevent Norm violation. In this paper we investigate a Stronger notion of Norm compliance that is evaluated over infinite traces. We show that it is not possible for all agents to be Strongly compliant with any arbitrary set of Norms. We then investigate situations when Strong Norm compliance can be guaranteed.
