29 research outputs found
The Fundamental Nature of the Log Loss Function
The standard loss functions used in the literature on probabilistic
prediction are the log loss function, the Brier loss function, and the
spherical loss function; however, any computable proper loss function can be
used for comparison of prediction algorithms. This note shows that the log loss
function is most selective in that any prediction algorithm that is optimal for
a given data sequence (in the sense of the algorithmic theory of randomness)
under the log loss function will be optimal under any computable proper mixable
loss function; on the other hand, there is a data sequence and a prediction
algorithm that is optimal for that sequence under either of the two other
standard loss functions but not under the log loss function.Comment: 12 page
On environment difficulty and discriminating power
The final publication is available at Springer via http://dx.doi.org/10.1007/s10458-014-9257-1This paper presents a way to estimate the difficulty and discriminating power of
any task instance. We focus on a very general setting for tasks: interactive (possibly multiagent)
environments where an agent acts upon observations and rewards. Instead of analysing
the complexity of the environment, the state space or the actions that are performed by the
agent, we analyse the performance of a population of agent policies against the task, leading
to a distribution that is examined in terms of policy complexity. This distribution is then
sliced by the algorithmic complexity of the policy and analysed through several diagrams
and indicators. The notion of environment response curve is also introduced, by inverting the
performance results into an ability scale. We apply all these concepts, diagrams and indicators
to two illustrative problems: a class of agent-populated elementary cellular automata, showing
how the difficulty and discriminating power may vary for several environments, and a multiagent
system, where agents can become predators or preys, and may need to coordinate.
Finally, we discuss how these tools can be applied to characterise (interactive) tasks and
(multi-agent) environments. These characterisations can then be used to get more insight
about agent performance and to facilitate the development of adaptive tests for the evaluation
of agent abilities.I thank the reviewers for their comments, especially those aiming at a clearer connection with the field of multi-agent systems and the suggestion of better approximations for the calculation of the response curves. The implementation of the elementary cellular automata used in the environments is based on the library 'CellularAutomaton' by John Hughes for R [58]. I am grateful to Fernando Soler-Toscano for letting me know about their work [65] on the complexity of 2D objects generated by elementary cellular automata. I would also like to thank David L. Dowe for his comments on a previous version of this paper. 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Evaluation in artificial intelligence: From task-oriented to ability-oriented measurement
The final publication is available at Springer via http://dx.doi.org/ 10.1007/s10462-016-9505-7.The evaluation of artificial intelligence systems and components is crucial for the
progress of the discipline. In this paper we describe and critically assess the different ways
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Identifying Flexible Pool Pumps Suitable for Distributed Demand Response Schemes
Demand response will be an important tool as non-dispatchable generation is added to the grid. Swimming pool filtration pumps are a promising appliance for the grid operator to control because, unlike air conditioners, their time of operation can be shifted by a day without affecting their primary role. Although many customers set and forget the timer settings, this paper studies smart meter data and demonstrates that many change the settings frequently. A "care index" is proposed that quantifies how much a customer appears to care about the precise timing of pump operation, which indicates how willing they are likely to be to relinquish control to the grid operator
An Information-Theoretic Predictive Model for the Accuracy of AI Agents Adapted from Psychometrics
A Data-driven Model of Nucleosynthesis with Chemical Tagging in a Lower-dimensional Latent Space
Chemical tagging seeks to identify unique star formation sites from present-day stellar abundances. Previous techniques have treated each abundance dimension as being statistically independent, despite theoretical expectations that many elements can be produced by more than one nucleosynthetic process. In this work, we introduce a data-driven model of nucleosynthesis, where a set of latent factors (e.g., nucleosynthetic yields) contribute to all stars with different scores and clustering (e.g., chemical tagging) is modeled by a mixture of multivariate Gaussians in a lower-dimensional latent space. We use an exact method to simultaneously estimate the factor scores for each star, the partial assignment of each star to each cluster, and the latent factors common to all stars, even in the presence of missing data entries. We use an information-theoretic Bayesian principle to estimate the number of latent factors and clusters. Using the second Galah data release, we find that six latent factors are preferred to explain N = 2566 stars with 17 chemical abundances. We identify the rapid- and slow neutron-capture processes, as well as latent factors consistent with Fe-peak and α-element production, and another where K and Zn dominate. When we consider N ∼ 160,000 stars with missing abundances, we find another seven factors, as well as 16 components in latent space. Despite these components showing separation in chemistry, which is explained through different yield contributions, none show significant structure in their positions or motions. We argue that more data and joint priors on cluster membership that are constrained by dynamical models are necessary to realize chemical tagging at a galactic-scale. We release accompanying software that scales well with the available data, allowing for the model's parameters to be optimized in seconds given a fixed number of latent factors, components, and ∼107 abundance measurements
Role of the NO-cGMP pathway in the muscarinic regulation of the L-type Ca2+ current in human atrial myocytes
The whole-cell patch-clamp technique was used to examine the participation of nitric oxide synthase (NOS) and soluble guanylyl cyclase in the muscarinic regulation of the L-type Ca2+ current (ICa) in freshly isolated human atrial myocytes.Acetylcholine (ACh, 1 μM) decreased basal ICa by 39.1 ± 5.5 % (n= 8) under control conditions, and by 38.0 ± 6.1 % (n= 6) in the presence of 1H-[1,2,4]oxadiazolo[4,3-a]quinoxaline-1-one (ODQ, 10 μM), a potent guanylyl cyclase inhibitor, and NG-monomethyl-L-arginine (L-NMMA, 1 mM), a competitive NOS inhibitor. L-NMMA alone had no effect on ICa, whilst ODQ increased ICa in 50 % of the cells.The accentuated antagonism of ACh on ICa, i.e. its ability to antagonize the stimulatory effect of β-adrenergic agonists and, by extension, of other cAMP-elevating agents, was examined after the current was stimulated by either the β-adrenergic agonist isoprenaline (Iso) or serotonin (5-HT). ACh (100 nM or 1 μM) completely blocked the stimulatory effects of 10 nM Iso or 10 nM 5-HT on ICa.Extracellular application of Methylene Blue (MBlue, 10 μM), a guanylyl cyclase inhibitor, antagonized the inhibitory effect of 1 μM ACh on Iso- or 5-HT-stimulated ICa. However, this effect was overcome by a 100-fold higher ACh concentration and was not mimicked by an intracellular application of MBlue.Inhibition of NOS and soluble guanylyl cyclase activities by addition of ODQ (10 μM) and L-NMMA (1 mM) to both extracellular and intracellular solutions, or by a 2 h pre-incubation of the cells with these inhibitors, modified neither the Iso (10 nM) response nor the inhibitory effect of ACh (100 nM or 1 μM) on Iso-stimulated ICa.Extracellular application of the NO donor SNAP (S-nitroso-N-acetyl-d,l-penicillamine) at 100 nM produced a stimulatory effect on ICa in control conditions. This stimulatory effect was abolished by intracellular MBlue (20 μM) or by intracellular and extracellular application of ODQ (10 μM) in combination with L-NMMA (1 mM).We conclude that the NO-cGMP pathway does not contribute significantly to the muscarinic regulation of ICa in human atrial myocytes