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Joah R. Madden - One of the best experts on this subject based on the ideXlab platform.
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A single factor explanation for associative learning performance on colour discrimination problems in common pheasants (Phasianus colchicus).
Intelligence, 2019Co-Authors: Jayden O. Van Horik, Ellis J. G. Langley, Mark A. Whiteside, Joah R. MaddenAbstract:It remains unclear whether performance of non-human animals on cognitive test batteries can be explained by domain general cognitive processes, as is found in humans. The persistence of this dispute is likely to stem from a lack of clarity of the psychological or neural processes involved. One broadly accepted cognitive process, that may predict performance in a range of psychometric tasks, is associative learning. We therefore investigated intra-individual performances on tasks that incorporate processes of associative learning, by assessing the speed of acquisition and reversal learning in up to 187 pheasants (Phasianus colchicus) on four related binary colour discrimination tasks. We found a strong, positive significant bivariate relationship between an individual's acquisition and reversal learning performances on one cue set. Weak, positive significant bivariate relationships were also found between an individual's performance on pairs of reversal tasks and between the acquisition and reversal performances on different cue sets. A single factor, robust to parallel analysis, explained 36% of variation in performance across tasks. Inter-individual variation could not be explained by differential prior experience, age, sex or body condition. We propose that a single factor explanation, which we call 'a', summarises the covariance among scores obtained from these visual discrimination tasks, as they all assess capacities for associative learning. We argue that 'a' may represent an underlying cognitive ability exhibited by an individual, which manifests across a variety of tasks requiring associative processes.
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The relationship between social rank and spatial learning in pheasants, Phasianus colchicus: cause or consequence?
PeerJ, 2018Co-Authors: Ellis J. G. Langley, Jayden O. Van Horik, Mark A. Whiteside, Christine E. Beardsworth, Joah R. MaddenAbstract:Individual differences in performances on cognitive tasks have been found to differ according to social rank across multiple species. However, it is not clear whether an individual's cognitive performance is flexible and the result of their current social rank, modulated by social interactions (social state dependent hypothesis), or if it is determined prior to the formation of the social hierarchy and indeed influences an individual's rank (prior attributes hypothesis). We separated these two hypotheses by measuring learning performance of male pheasants, Phasianus colchicus, on a spatial discrimination task as chicks and again as adults. We inferred adult male social rank from observing agonistic interactions while housed in captive multi-male multi-female groups. Learning performance of adult males was assayed after social rank had been standardised; by housing single males with two or four females. We predicted that if cognitive abilities determine social rank formation we would observe: consistency between chick and adult performances on the cognitive task and chick performance would predict adult social rank. We found that learning performances were consistent from chicks to adults for task accuracy, but not for speed of learning and chick learning performances were not related to adult social rank. Therefore, we could not support the prior attributes hypothesis of cognitive abilities aiding social rank formation. Instead, we found that individual differences in learning performances of adults were predicted by the number of females a male was housed with; males housed with four females had higher levels of learning performance than males housed with two females; and their most recent recording of captive social rank, even though learning performance was assayed while males were in a standardized, non-competitive environment. This does not support the hypothesis that direct social pressures are causing the inter-individual variation in learning performances that we observe. Instead, our results suggest that there may be carry-over effects of aggressive social interactions on learning performance. Consequently, whether early life spatial learning performances influence social rank is unclear but these performances are modulated by the current social environment and a male's most recent social rank.
Christine E. Beardsworth - One of the best experts on this subject based on the ideXlab platform.
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The relationship between social rank and spatial learning in pheasants, Phasianus colchicus: cause or consequence?
PeerJ, 2018Co-Authors: Ellis J. G. Langley, Jayden O. Van Horik, Mark A. Whiteside, Christine E. Beardsworth, Joah R. MaddenAbstract:Individual differences in performances on cognitive tasks have been found to differ according to social rank across multiple species. However, it is not clear whether an individual's cognitive performance is flexible and the result of their current social rank, modulated by social interactions (social state dependent hypothesis), or if it is determined prior to the formation of the social hierarchy and indeed influences an individual's rank (prior attributes hypothesis). We separated these two hypotheses by measuring learning performance of male pheasants, Phasianus colchicus, on a spatial discrimination task as chicks and again as adults. We inferred adult male social rank from observing agonistic interactions while housed in captive multi-male multi-female groups. Learning performance of adult males was assayed after social rank had been standardised; by housing single males with two or four females. We predicted that if cognitive abilities determine social rank formation we would observe: consistency between chick and adult performances on the cognitive task and chick performance would predict adult social rank. We found that learning performances were consistent from chicks to adults for task accuracy, but not for speed of learning and chick learning performances were not related to adult social rank. Therefore, we could not support the prior attributes hypothesis of cognitive abilities aiding social rank formation. Instead, we found that individual differences in learning performances of adults were predicted by the number of females a male was housed with; males housed with four females had higher levels of learning performance than males housed with two females; and their most recent recording of captive social rank, even though learning performance was assayed while males were in a standardized, non-competitive environment. This does not support the hypothesis that direct social pressures are causing the inter-individual variation in learning performances that we observe. Instead, our results suggest that there may be carry-over effects of aggressive social interactions on learning performance. Consequently, whether early life spatial learning performances influence social rank is unclear but these performances are modulated by the current social environment and a male's most recent social rank.
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The relationship between social rank and spatial learning in pheasants, Phasianus colchicus: Cause or consequence? (article)
'PeerJ', 2018Co-Authors: Langley Ejg, Jo ,van Horik, Christine E. BeardsworthAbstract:This is the final version. Available from PeerJ via the DOI in this record.The dataset associated with this article is in ORE: https://doi.org/10.24378/exe.143Individual differences in performances on cognitive tasks have been found to differ according to social rank across multiple species. However, it is not clear whether an individual's cognitive performance is flexible and the result of their current social rank, modulated by social interactions (social state dependent hypothesis), or if it is determined prior to the formation of the social hierarchy and indeed influences an individual's rank (prior attributes hypothesis). We separated these two hypotheses by measuring learning performance of male pheasants, Phasianus colchicus, on a spatial discrimination task as chicks and again as adults. We inferred adult male social rank from observing agonistic interactions while housed in captive multi-male multi-female groups. Learning performance of adult males was assayed after social rank had been standardised; by housing single males with two or four females. We predicted that if cognitive abilities determine social rank formation we would observe: consistency between chick and adult performances on the cognitive task and chick performance would predict adult social rank. We found that learning performances were consistent from chicks to adults for task accuracy, but not for speed of learning and chick learning performances were not related to adult social rank. Therefore, we could not support the prior attributes hypothesis of cognitive abilities aiding social rank formation. Instead, we found that individual differences in learning performances of adults were predicted by the number of females a male was housed with; males housed with four females had higher levels of learning performance than males housed with two females; and their most recent recording of captive social rank, even though learning performance was assayed while males were in a standardized, non-competitive environment. This does not support the hypothesis that direct social pressures are causing the inter-individual variation in learning performances that we observe. Instead, our results suggest that there may be carry-over effects of aggressive social interactions on learning performance. Consequently, whether early life spatial learning performances influence social rank is unclear but these performances are modulated by the current social environment and a male's most recent social rank.European Research Counci
Ellis J. G. Langley - One of the best experts on this subject based on the ideXlab platform.
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A single factor explanation for associative learning performance on colour discrimination problems in common pheasants (Phasianus colchicus).
Intelligence, 2019Co-Authors: Jayden O. Van Horik, Ellis J. G. Langley, Mark A. Whiteside, Joah R. MaddenAbstract:It remains unclear whether performance of non-human animals on cognitive test batteries can be explained by domain general cognitive processes, as is found in humans. The persistence of this dispute is likely to stem from a lack of clarity of the psychological or neural processes involved. One broadly accepted cognitive process, that may predict performance in a range of psychometric tasks, is associative learning. We therefore investigated intra-individual performances on tasks that incorporate processes of associative learning, by assessing the speed of acquisition and reversal learning in up to 187 pheasants (Phasianus colchicus) on four related binary colour discrimination tasks. We found a strong, positive significant bivariate relationship between an individual's acquisition and reversal learning performances on one cue set. Weak, positive significant bivariate relationships were also found between an individual's performance on pairs of reversal tasks and between the acquisition and reversal performances on different cue sets. A single factor, robust to parallel analysis, explained 36% of variation in performance across tasks. Inter-individual variation could not be explained by differential prior experience, age, sex or body condition. We propose that a single factor explanation, which we call 'a', summarises the covariance among scores obtained from these visual discrimination tasks, as they all assess capacities for associative learning. We argue that 'a' may represent an underlying cognitive ability exhibited by an individual, which manifests across a variety of tasks requiring associative processes.
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The relationship between social rank and spatial learning in pheasants, Phasianus colchicus: cause or consequence?
PeerJ, 2018Co-Authors: Ellis J. G. Langley, Jayden O. Van Horik, Mark A. Whiteside, Christine E. Beardsworth, Joah R. MaddenAbstract:Individual differences in performances on cognitive tasks have been found to differ according to social rank across multiple species. However, it is not clear whether an individual's cognitive performance is flexible and the result of their current social rank, modulated by social interactions (social state dependent hypothesis), or if it is determined prior to the formation of the social hierarchy and indeed influences an individual's rank (prior attributes hypothesis). We separated these two hypotheses by measuring learning performance of male pheasants, Phasianus colchicus, on a spatial discrimination task as chicks and again as adults. We inferred adult male social rank from observing agonistic interactions while housed in captive multi-male multi-female groups. Learning performance of adult males was assayed after social rank had been standardised; by housing single males with two or four females. We predicted that if cognitive abilities determine social rank formation we would observe: consistency between chick and adult performances on the cognitive task and chick performance would predict adult social rank. We found that learning performances were consistent from chicks to adults for task accuracy, but not for speed of learning and chick learning performances were not related to adult social rank. Therefore, we could not support the prior attributes hypothesis of cognitive abilities aiding social rank formation. Instead, we found that individual differences in learning performances of adults were predicted by the number of females a male was housed with; males housed with four females had higher levels of learning performance than males housed with two females; and their most recent recording of captive social rank, even though learning performance was assayed while males were in a standardized, non-competitive environment. This does not support the hypothesis that direct social pressures are causing the inter-individual variation in learning performances that we observe. Instead, our results suggest that there may be carry-over effects of aggressive social interactions on learning performance. Consequently, whether early life spatial learning performances influence social rank is unclear but these performances are modulated by the current social environment and a male's most recent social rank.
Jayden O. Van Horik - One of the best experts on this subject based on the ideXlab platform.
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A single factor explanation for associative learning performance on colour discrimination problems in common pheasants (Phasianus colchicus).
Intelligence, 2019Co-Authors: Jayden O. Van Horik, Ellis J. G. Langley, Mark A. Whiteside, Joah R. MaddenAbstract:It remains unclear whether performance of non-human animals on cognitive test batteries can be explained by domain general cognitive processes, as is found in humans. The persistence of this dispute is likely to stem from a lack of clarity of the psychological or neural processes involved. One broadly accepted cognitive process, that may predict performance in a range of psychometric tasks, is associative learning. We therefore investigated intra-individual performances on tasks that incorporate processes of associative learning, by assessing the speed of acquisition and reversal learning in up to 187 pheasants (Phasianus colchicus) on four related binary colour discrimination tasks. We found a strong, positive significant bivariate relationship between an individual's acquisition and reversal learning performances on one cue set. Weak, positive significant bivariate relationships were also found between an individual's performance on pairs of reversal tasks and between the acquisition and reversal performances on different cue sets. A single factor, robust to parallel analysis, explained 36% of variation in performance across tasks. Inter-individual variation could not be explained by differential prior experience, age, sex or body condition. We propose that a single factor explanation, which we call 'a', summarises the covariance among scores obtained from these visual discrimination tasks, as they all assess capacities for associative learning. We argue that 'a' may represent an underlying cognitive ability exhibited by an individual, which manifests across a variety of tasks requiring associative processes.
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The relationship between social rank and spatial learning in pheasants, Phasianus colchicus: cause or consequence?
PeerJ, 2018Co-Authors: Ellis J. G. Langley, Jayden O. Van Horik, Mark A. Whiteside, Christine E. Beardsworth, Joah R. MaddenAbstract:Individual differences in performances on cognitive tasks have been found to differ according to social rank across multiple species. However, it is not clear whether an individual's cognitive performance is flexible and the result of their current social rank, modulated by social interactions (social state dependent hypothesis), or if it is determined prior to the formation of the social hierarchy and indeed influences an individual's rank (prior attributes hypothesis). We separated these two hypotheses by measuring learning performance of male pheasants, Phasianus colchicus, on a spatial discrimination task as chicks and again as adults. We inferred adult male social rank from observing agonistic interactions while housed in captive multi-male multi-female groups. Learning performance of adult males was assayed after social rank had been standardised; by housing single males with two or four females. We predicted that if cognitive abilities determine social rank formation we would observe: consistency between chick and adult performances on the cognitive task and chick performance would predict adult social rank. We found that learning performances were consistent from chicks to adults for task accuracy, but not for speed of learning and chick learning performances were not related to adult social rank. Therefore, we could not support the prior attributes hypothesis of cognitive abilities aiding social rank formation. Instead, we found that individual differences in learning performances of adults were predicted by the number of females a male was housed with; males housed with four females had higher levels of learning performance than males housed with two females; and their most recent recording of captive social rank, even though learning performance was assayed while males were in a standardized, non-competitive environment. This does not support the hypothesis that direct social pressures are causing the inter-individual variation in learning performances that we observe. Instead, our results suggest that there may be carry-over effects of aggressive social interactions on learning performance. Consequently, whether early life spatial learning performances influence social rank is unclear but these performances are modulated by the current social environment and a male's most recent social rank.
Shmuel Boyarski - One of the best experts on this subject based on the ideXlab platform.
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Polytopic best-mean H∞ performance analysis
International Journal of Systems Science, 2013Co-Authors: Shmuel BoyarskiAbstract:In Boyarski and Shaked [2005, ‘Robust H ∞ Control Design for Best Mean Performance Over an Uncertain-parameters Box’, Systems and Control Letters , 54, 585–595], a novel best-mean approach to robust analysis and control over uncertain-parameters boxes was presented. This article extends the results of Boyarski and Shaked 2005 to convex uncertainty polytopes of arbitrary shape and arbitrary number of vertices, without an underlying parameters model. The article addresses robust, polytopic, probabilistic H ∞ analysis of linear systems and focuses on the performance distribution over the uncertainty region rather than just on the performance bound, as is customary in robust control. It is assumed that all system instances over the uncertainty polytope may occur with equal probability; this uniform distribution assumption is common in robust statistical analysis and is known to be conservative. The proposed approach considers different disturbance attenuation levels DALs at the vertices of the uncertainty polytope. It is shown that, under the latter assumption, the mean DAL over the polytope is the algebraic average of the DALs at the polytope's vertices. Thus, the mean DAL over the polytope can be optimised by minimising the sum of the DALs at the vertices. The standard deviation of the DAL over the uncertainty polytope is also addressed, and a method to minimise this standard deviation in order to enforce uniform performance over the polytope is shown. The example utilises a state-feedback synthesis theorem presented in Boyarski and Shaked 2005. A Monte-Carlo analysis verifies correct statistics of the resulting closed-loop ‘pointwise’ H ∞-norms over the uncertainty region, and highlights the differences from a corresponding bound minimisation: a marginally higher bound, but much better mean and variance.
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Polytopic best-mean H ∞ performance analysis
2008Co-Authors: Shmuel BoyarskiAbstract:In [1], a novel best-mean approach to robust analysis and control over uncertain-parameters boxes was presented. This paper extends the results of [1] to convex uncertainty polytopes of arbitrary shape and arbitrary number of vertices, without an underlying parameters model. The paper addresses robust, polytopic, probabilistic H∞ analysis of linear systems and focuses on the performance distribution over the uncertainty region (rather than just on the performance bound, as is customary in robust control). It is assumed that all system instances over the uncertainty polytope may occur with equal probability; this uniform distribution assumption is common in robust statistical analysis and is known to be conservative. The proposed approach considers different disturbance attenuation levels (DALs) at the vertices of the uncertainty polytope. It is shown that, under the latter assumption, the mean disturbance attenuation level (DAL) over the polytope is the algebraic average of the DALs at the polytope's vertices. Thus, the mean DAL over the polytope can be optimized by minimizing the sum of the DALs at the vertices. The standard deviation of the DAL over the uncertain parameters-box is also addressed, and a method to minimize this standard deviation (in order to enforce uniform performance over the polytope) is shown. The state-feedback design example utilizes a theorem presented in [1]. A Monte-Carlo analysis verifies the statistics of the resulting closed-loop 'pointwise' H∞-norms over the uncertainty region.
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PROBABILITY-GUARANTEED ROBUST H∞ PERFORMANCE ANALYSIS
IFAC Proceedings Volumes, 2002Co-Authors: Isaac Yaesh, Shmuel Boyarski, Uri ShakedAbstract:Abstract This paper addresses the common engineering practice of specifying a required probability of attaining some performance level. The problem setup is that of a standard robust H ∞ performance analysis of a parameter-dependent system, except that the parameter hyper-rectangle (box) shrinks in the analysis in order to accommodate a polytopic performance goal that is better than the one attainable for the original parameter box. An affine-quadratic, multiconvex approach is applied to reduce the overdesign that is inherent in the quadratic approach. A version of the Bounded Real Lemma (BRL) in the form of BiLinear Matrix Inequalities (BLMIs) guarantees a minimum H ∞ -norm for a prescribed probability. These BLMIs are solved using an iterative algorithm. A uniform distribution is assumed for the system parameters, according to the uniformity principle. The probability requirement is expressed by a set of LMIs that is derived by extending an existing second-order cone method; these LMIs are to be concurrently solved with the BRL BLMIs. The proposed analysis is demonstrated via a 2-parameter example. Copyright © 2002 IFAC
