Multiscale stochastic approximation for parametric optimization of hidden Markov models

A two-time scale stochastic approximation algorithm is proposed for simulation-based parametric optimization of hidden Markov models, as an alternative to the traditional approaches to ''infinitesimal perturbation analysis.'' Its convergence is analyzed, and a queueing example is presented.

Reinforcement Learning With Function Approximation for Traffic Signal Control

We propose, for the first time, a reinforcement learning (RL) algorithm with function approximation for traffic signal control. Our algorithm incorporates state-action features and is easily implementable in high-dimensional settings. Prior work, e. g., the work of Abdulhai et al., on the application of RL to traffic signal control requires full-state representations and cannot be implemented, even in moderate-sized road networks, because the computational complexity exponentially grows in the numbers of lanes and junctions. We tackle this problem of the curse of dimensionality by effectively using feature-based state representations that use a broad characterization of the level of congestion as low, medium, or high. One advantage of our algorithm is that, unlike prior work based on RL, it does not require precise information on queue lengths and elapsed times at each lane but instead works with the aforementioned described features. The number of features that our algorithm requires is linear to the number of signaled lanes, thereby leading to several orders of magnitude reduction in the computational complexity. We perform implementations of our algorithm on various settings and show performance comparisons with other algorithms in the literature, including the works of Abdulhai et al. and Cools et al., as well as the fixed-timing and the longest queue algorithms. For comparison, we also develop an RL algorithm that uses full-state representation and incorporates prioritization of traffic, unlike the work of Abdulhai et al. We observe that our algorithm outperforms all the other algorithms on all the road network settings that we consider.

Strong shock approximation in the new theory of shock dynamics

This paper investigates the propagation of a strong shock into an inhomogeneous medium using the new theory of shock dynamics. The equations are simple to solve and involve no trial-and-error method commonly used in this case. The results compare favourably with earlier results obtained in the case of self-similar flows, which arise as a special case of this theory.

The actor-critic algorithm as multi-time-scale stochastic approximation

The actor-critic algorithm of Barto and others for simulation-based optimization of Markov decision processes is cast as a two time Scale stochastic approximation. Convergence analysis, approximation issues and an example are studied.

Spiroannulation of a cyclopentane ring. Synthesis of spiro[4.n](n+5)alk-2-en-1-ones

A methodology based on Claisen rearrangement-Wacker oxidation and intramolecular aldol condensation strategy starting from cyclic ketones leading to spiro[4.n](n+5)alk-2-en-1-ones has been developed. Thus one-pot Claisen rearrangement of the alkyl alcohols 6a-c furnished the aldehydes 8a-c, which on regiospecific oxidation using Wacker conditions generated the keto-aldehydes 9a-c. Finally, intramolecular aldol condensation transformed the keto-aldehydes 9a-c into spiroannulated products 10a-c.

Providing quality of service via opportunistic splitting using stochastic approximation

We consider the problem of wireless channel allocation to multiple users. A slot is given to a user with a highest metric (e.g., channel gain) in that slot. The scheduler may not know the channel states of all the users at the beginning of each slot. In this scenario opportunistic splitting is an attractive solution. However this algorithm requires that the metrics of different users form independent, identically distributed (iid) sequences with same distribution and that their distribution and number be known to the scheduler. This limits the usefulness of opportunistic splitting. In this paper we develop a parametric version of this algorithm. The optimal parameters of the algorithm are learnt online through a stochastic approximation scheme. Our algorithm does not require the metrics of different users to have the same distribution. The statistics of these metrics and the number of users can be unknown and also vary with time. Each metric sequence can be Markov. We prove the convergence of the algorithm and show its utility by scheduling the channel to maximize its throughput while satisfying some fairness and/or quality of service constraints.

Opportunistic splitting for scheduling via stochastic approximation

We consider the problem of scheduling a wireless channel among multiple users. A slot is given to a user with a highest metric (e.g., channel gain) in that slot. The scheduler may not know the channel states of all the users at the beginning of each slot. In this scenario opportunistic splitting is an attractive solution. However this algorithm requires that the metrics of different users form independent, identically distributed (iid) sequences with same distribution and that their distribution and number be known to the scheduler. This limits the usefulness of opportunistic splitting. In this paper we develop a parametric version of this algorithm. The optimal parameters of the algorithm are learnt online through a stochastic approximation scheme. Our algorithm does not require the metrics of different users to have the same distribution. The statistics of these metrics and the number of users can be unknown and also vary with time. We prove the convergence of the algorithm and show its utility by scheduling the channel to maximize its throughput while satisfying some fairness and/or quality of service constraints.

A comparison of the DNMR behaviour of methyl 5,6-bis(2-methoxyphenyl)-1,4-dimethyl-7-oxobicyclo[2.2.1]hept-5-en-2-endo-carboxylate and its 7-oxa analogue

Methyl 5,6-Bis(2-methoxyphenyt)-1,4-dimethyl-7-oxobicyclo[2.2.1]hept-5-en-2-endo-carboxylate, a moderately crowded norbornenone ester, exhibits complex VT-DNMR behaviour. A similar behaviour is not seen in its 7-oxa analogue, showing that conformational transmission from position 7 has a crucial influence on the distance parameters that govern the dynamic processes involving the substituents on the bicycloheptene framework.

Pseudodynamic systems approach based on a quadratic approximation of update equations for diffuse optical tomography

We explore a pseudodynamic form of the quadratic parameter update equation for diffuse optical tomographic reconstruction from noisy data. A few explicit and implicit strategies for obtaining the parameter updates via a semianalytical integration of the pseudodynamic equations are proposed. Despite the ill-posedness of the inverse problem associated with diffuse optical tomography, adoption of the quadratic update scheme combined with the pseudotime integration appears not only to yield higher convergence, but also a muted sensitivity to the regularization parameters, which include the pseudotime step size for integration. These observations are validated through reconstructions with both numerically generated and experimentally acquired data. (C) 2011 Optical Society of America

Theory of Gas Hydrates: Effect of the Approximation of Rigid Water Lattice

One of the assumptions of the van der Waals and Platteeuw theory for gas hydrates is that the host water lattice is rigid and not distorted by the presence of guest molecules. In this work, we study the effect of this approximation on the triple-point lines of the gas hydrates. We calculate the triple-point lines of methane and ethane hydrates via Monte Carlo molecular simulations and compare the simulation results with the predictions of van der Waals and Platteeuw theory. Our study shows that even if the exact intermolecular potential between the guest molecules and water is known, the dissociation temperatures predicted by the theory are significantly higher. This has serious implications to the modeling of gas hydrate thermodynamics, and in spite of the several impressive efforts made toward obtaining an accurate description of intermolecular interactions in gas hydrates, the theory will suffer from the problem of robustness if the issue of movement of water molecules is not adequately addressed.

(2E)-1-(5-Chlorothiophen-2-yl)-3-(2,4,5-trimethoxyphenyl)prop-2-en-1-one

In the title molecule, C(16)H(15)ClO(4)S, the chlorothiophene and trimethoxyphenyl rings make a dihedral angle of 31.12 (5)degrees. The C = C double bond exhibits an E conformation. In the crystal, C-H center dot center dot center dot O interactions generate bifurcated bonds, linking the molecules into chains along the b axis.

Explorations en route to synthesis of tashironins: singlet oxygen cycloaddition to 1,3-cyclopentadienes embedded within allo-cedrane framework

In an approach directed toward a tashironin based complex natural product, efficacy of the singlet oxygen mediated [4+2]-cycloaddition to a tetracyclic cyclopentadiene has been evaluated to install the key cis-1,4-dihydroxy functionality. (C) 2011 Elsevier Ltd. All rights reserved.

(2E)-1-(5-Chlorothiophen-2-yl)-3-(2,3-dimethoxyphenyl)prop-2-en-1-one

In the title compound, C(15)H(13)ClO(3)S, the chlorothiophene and dimethoxyphenyl groups are linked by a prop-2-en-1-one group. The C=C double bond exhibits an E conformation. The molecule is non-planar, with a dihedral angle of 31.12 (5)degrees between the chlorothiophene and dimethoxyphenyl rings. The methoxy group at position 3 is coplanar with the benzene ring to which it is attached, with a C-O-C-C torsion angle of -3.8 (3)degrees. The methoxy group attached at position 2 of the benzene ring is in a (+)synclinal conformation, as indicated by the C-O-C-C torsion angle of -73.6 (2)degrees. In the crystal, two different C-H center dot center dot center dot O intermolecular interactions generate chains of molecules extending along the b axis.