The Experts below are selected from a list of 67113 Experts worldwide ranked by ideXlab platform
Moshe Y Vardi - One of the best experts on this subject based on the ideXlab platform.
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solving partial information stochastic parity games
Logic in Computer Science, 2013Co-Authors: Sumit Nain, Moshe Y VardiAbstract:We study one-sided partial-information 2-player concurrent stochastic games with parity objectives. In such a game, one of the players has only partial visibility of the state of the game, while the other player has complete knowledge. In general, such games are known to be undecidable, even for the case of a single player (POMDP). These undecidability results depend crucially on player strategies that exploit an infinite amount of Memory. However, in many applications of games, one is usually more interested in finding a finite-Memory Strategy. We consider the problem of whether the player with partial information has a finite-Memory winning Strategy when the player with complete information is allowed to use an arbitrary amount of Memory. We show that this problem is decidable.
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LICS - Solving Partial-Information Stochastic Parity Games
2013 28th Annual ACM IEEE Symposium on Logic in Computer Science, 2013Co-Authors: Sumit Nain, Moshe Y VardiAbstract:We study one-sided partial-information 2-player concurrent stochastic games with parity objectives. In such a game, one of the players has only partial visibility of the state of the game, while the other player has complete knowledge. In general, such games are known to be undecidable, even for the case of a single player (POMDP). These undecidability results depend crucially on player strategies that exploit an infinite amount of Memory. However, in many applications of games, one is usually more interested in finding a finite-Memory Strategy. We consider the problem of whether the player with partial information has a finite-Memory winning Strategy when the player with complete information is allowed to use an arbitrary amount of Memory. We show that this problem is decidable.
Sumit Nain - One of the best experts on this subject based on the ideXlab platform.
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solving partial information stochastic parity games
Logic in Computer Science, 2013Co-Authors: Sumit Nain, Moshe Y VardiAbstract:We study one-sided partial-information 2-player concurrent stochastic games with parity objectives. In such a game, one of the players has only partial visibility of the state of the game, while the other player has complete knowledge. In general, such games are known to be undecidable, even for the case of a single player (POMDP). These undecidability results depend crucially on player strategies that exploit an infinite amount of Memory. However, in many applications of games, one is usually more interested in finding a finite-Memory Strategy. We consider the problem of whether the player with partial information has a finite-Memory winning Strategy when the player with complete information is allowed to use an arbitrary amount of Memory. We show that this problem is decidable.
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LICS - Solving Partial-Information Stochastic Parity Games
2013 28th Annual ACM IEEE Symposium on Logic in Computer Science, 2013Co-Authors: Sumit Nain, Moshe Y VardiAbstract:We study one-sided partial-information 2-player concurrent stochastic games with parity objectives. In such a game, one of the players has only partial visibility of the state of the game, while the other player has complete knowledge. In general, such games are known to be undecidable, even for the case of a single player (POMDP). These undecidability results depend crucially on player strategies that exploit an infinite amount of Memory. However, in many applications of games, one is usually more interested in finding a finite-Memory Strategy. We consider the problem of whether the player with partial information has a finite-Memory winning Strategy when the player with complete information is allowed to use an arbitrary amount of Memory. We show that this problem is decidable.
Laurence Taconnat - One of the best experts on this subject based on the ideXlab platform.
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Optimizing Memory Strategy use in young and older adults: The role of metaMemory and internal Strategy use
Acta Psychologica, 2019Co-Authors: Lina Guerrero Sastoque, Michel Isingrini, Badiâa Bouazzaoui, Lucile Burger, Charlotte Froger, Laurence TaconnatAbstract:We explored whether experiencing differential efficacy of reading and generation for Memory in an initial learning trial led younger and older adults to improve recall of read items in a subsequent learning trial, leading to a reduction of the generation effect. In the first trial, generation improved the Memory performance of both young and older adults. However, in Trial 2, the generation effect remained significant for older adults only, confirming that they did not change the way they processed read items, unlike the young adults. The older adults were also less spontaneously aware that generation led to better Memory performance in the first trial, and, in contrast to the young adults, awareness did not result in a reduction of the generation effect. Moreover, the age-related differences in generation effect reduction were mediated by an independent measure of self-reported internal Strategy use. However, when an appropriate environmental support was provided between both trials, older adults improved read items recall at the second trial as well as younger ones, leading to an elimination of the generation advantage for both groups. Environmental support reduced the implication of internal Strategy use in the generation effect reduction, suggesting that age-related differences in the implementation of effective encoding processes in Trial 2 would be the consequence of a metaMemory deficit, and reduced capacity to self-initiate internal strategies.
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Sequential difficulty effects during execution of Memory strategies in young and older adults
Memory, 2015Co-Authors: Kim Uittenhove, Lucile Burger, Laurence Taconnat, Patrick LemaireAbstract:This study aimed at uncovering factors influencing execution of Memory strategies and at furthering our understanding of ageing effects on Memory performance. To achieve this end, we investigated Strategy sequential difficulty (SSD) effects recently demonstrated by Uittenhove and Lemaire in the domain of problem solving. We found that both young and older participants correctly recalled more words using a sentence-construction Strategy when this Strategy followed an easier Strategy (i.e., repetition Strategy) or a harder Strategy (i.e., mental-image Strategy). These SSD effects were of equal magnitude in young and older adults, correlated significantly with Stroop performance in both young and older adults and correlated with N-back performance only in young adults. These findings have important implications for furthering our understanding of Memory Strategy execution and age-related variations in Memory performance, as well for understanding mechanisms underlying SSD effects.
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Aging and self-reported internal and external Memory Strategy uses: The role of executive functioning
Acta Psychologica, 2010Co-Authors: Badiâa Bouazzaoui, Michel Isingrini, Séverine Fay, Lucie Angel, Sandrine Vanneste, David Clarys, Laurence TaconnatAbstract:The aim of this study was to investigate the effect of advanced age on self-reported internal and external Memory Strategy uses, and whether this effect can be predicted by executive functioning. A sample of 194 participants aged 21 to 80 divided into three age groups (21–40, 41–60, 61–80) completed the two Strategy scales of the MetaMemory in Adulthood (MIA) questionnaire, differentiating between internal and external everyday Memory Strategy uses, and three tests of executive functioning. The results showed that: (1) the use of external Memory strategies increased with age, whereas use of internal Memory Strategy decreased; (2) executive functioning appeared to be related only to internal strategies, the participants who reported the greatest use of internal strategies having the highest executive level; and (3) executive functioning accounted for a sizeable proportion of the age-related variance in internal Strategy use. These findings suggest that older adults preferentially use external Memory strategies to cope with everyday Memory impairment due to aging. They also support the view that the age-related decrease in the implementation of internal Memory strategies can be explained by the executive hypothesis of cognitive aging. This result parallels those observed using objective laboratory Memory Strategy measures and then supports the validity of self-reported Memory Strategy questionnaire.
Patrick Lemaire - One of the best experts on this subject based on the ideXlab platform.
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Sequential difficulty effects during execution of Memory strategies in young and older adults
Memory, 2015Co-Authors: Kim Uittenhove, Lucile Burger, Laurence Taconnat, Patrick LemaireAbstract:This study aimed at uncovering factors influencing execution of Memory strategies and at furthering our understanding of ageing effects on Memory performance. To achieve this end, we investigated Strategy sequential difficulty (SSD) effects recently demonstrated by Uittenhove and Lemaire in the domain of problem solving. We found that both young and older participants correctly recalled more words using a sentence-construction Strategy when this Strategy followed an easier Strategy (i.e., repetition Strategy) or a harder Strategy (i.e., mental-image Strategy). These SSD effects were of equal magnitude in young and older adults, correlated significantly with Stroop performance in both young and older adults and correlated with N-back performance only in young adults. These findings have important implications for furthering our understanding of Memory Strategy execution and age-related variations in Memory performance, as well for understanding mechanisms underlying SSD effects.
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Working Memory, Strategy execution, and Strategy selection in mental arithmetic.
Quarterly Journal of Experimental Psychology, 2007Co-Authors: Ineke Imbo, Sandrine Duverne, Patrick LemaireAbstract:A total of 72 participants estimated products of complex multiplications of two-digit operands (e.g., 63 × 78), using two strategies that differed in complexity. The simple Strategy involved rounding both operands down to the closest decades (e.g., 60 × 70), whereas the complex Strategy required rounding both operands up to the closest decades (e.g., 70 × 80). Participants accomplished this estimation task in two conditions: a no-load condition and a working-Memory load condition in which executive components of working Memory were taxed. The choice/no-choice method was used to obtain unbiased Strategy execution and Strategy selection data. Results showed that loading working-Memory resources led participants to poorer Strategy execution. Additionally, participants selected the simple Strategy more often under working-Memory load. We discuss the implications of the results to further our understanding of variations in Strategy selection and execution, as well as our understanding of the impact of working-...
Yi Zhang - One of the best experts on this subject based on the ideXlab platform.
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urban road network modeling and real time prediction based on householder transformation and adjacent vector
International Symposium on Neural Networks, 2009Co-Authors: Shuo Deng, Jianming Hu, Yin Wang, Yi ZhangAbstract:This paper put forward a multivariate one-order-regression single road link model based on the algorithm of Householder Transformation to reduce the computation complexity in real-time prediction and to facilitate the study on network turn-ratio pattern evolution. Then the paper analyses the limitation of current urban road network model based on adjacent matrix and contributed a novel model based on new Memory Strategy aiming at reduce the Memory space occupied by adjacent matrix, carrying turn movement information in the storage and avoiding redundant calculation. To verify the new modeling method, the study involved in a field work on part of urban network in Beijing, China. In conclusion, the new modeling methods in this paper enhanced the performance of urban road modeling.
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ISNN (3) - Urban Road Network Modeling and Real-Time Prediction Based on Householder Transformation and Adjacent Vector
Advances in Neural Networks – ISNN 2009, 2009Co-Authors: Shuo Deng, Jianming Hu, Yin Wang, Yi ZhangAbstract:This paper put forward a multivariate one-order-regression single road link model based on the algorithm of Householder Transformation to reduce the computation complexity in real-time prediction and to facilitate the study on network turn-ratio pattern evolution. Then the paper analyses the limitation of current urban road network model based on adjacent matrix and contributed a novel model based on new Memory Strategy aiming at reduce the Memory space occupied by adjacent matrix, carrying turn movement information in the storage and avoiding redundant calculation. To verify the new modeling method, the study involved in a field work on part of urban network in Beijing, China. In conclusion, the new modeling methods in this paper enhanced the performance of urban road modeling.