Marginal multi-Bernoulli filters: RFS derivation of MHT, JIPDA and association-based MeMBer

Recent developments in random finite sets (RFSs) have yielded a variety of tracking methods that avoid data association. This paper derives a form of the full Bayes RFS filter and observes that data association is implicitly present, in a data structure similar to MHT. Subsequently, algorithms are obtained by approximating the distribution of associations. Two algorithms result: one nearly identical to JIPDA, and another related to the MeMBer filter. Both improve performance in challenging environments.Comment: Journal version at http://ieeexplore.ieee.org/document/7272821. Matlab code of simple implementation included with ancillary file

Hybrid Poisson and multi-Bernoulli filters

The probability hypothesis density (PHD) and multi-target multi-Bernoulli (MeMBer) filters are two leading algorithms that have emerged from random finite sets (RFS). In this paper we study a method which combines these two approaches. Our work is motivated by a sister paper, which proves that the full Bayes RFS filter naturally incorporates a Poisson component representing targets that have never been detected, and a linear combination of multi-Bernoulli components representing targets under track. Here we demonstrate the benefit (in speed of track initiation) that maintenance of a Poisson component of undetected targets provides. Subsequently, we propose a method of recycling, which projects Bernoulli components with a low probability of existence onto the Poisson component (as opposed to deleting them). We show that this allows us to achieve similar tracking performance using a fraction of the number of Bernoulli components (i.e., tracks).Comment: Submitted to 15th International Conference on Information Fusion (2012

Homeostatic plasticity improves signal propagation in continuous time recurrent neural networks

Continuous-time recurrent neural networks (CTRNNs) are potentially an excellent substrate for the generation of adaptive behaviour in artificial autonomous agents. However, node saturation effects in these networks can leave them insensitive to input and stop signals from propagating. Node saturation is related to the problems of hyper-excitation and quiescence in biological nervous systems, which are thought to be avoided through the existence of homeostatic plastic mechanisms. Analogous mechanisms are here implemented in a variety of CTRNN architectures and are shown to increase node sensitivity and improve signal propagation, with implications for robotics. These results lend support to the view that homeostatic plasticity may prevent quiescence and hyper-excitation in biological nervous systems

Farmers’ Willingness to Grow Switchgrass as a Cellulosic Bioenergy Crop: A Stated Choice Approach

Farmers’ Willingness to Grow Switchgrass as a Cellulosic Bioenergy Crop: A Stated Choice Approach Agriculture’s role as a source of feedstocks in a potential lignocellulosic-based biofuel industry is a critical economic issue. Several studies have assessed the technical feasibility of producing bioenergy crops on agricultural lands. However, few of these studies have assessed farmers’ willingness to produce or supply bioenergy crops or crop residues. Biomass markets for bioenergy crops do not exist, and developing these markets may take several years. Therefore, an important, yet unaddressed question is under what contractual or pricing arrangements farmers will grow biomass for bioenergy in these nascent markets. The purpose of this paper is to examine farmers’ willingness to produce switchgrass under alternative contractual, pricing, and harvesting arrangements. Contracts are likely to be the preferred method to bring together producers and processors of biomass for bioenergy. Contract design may vary across farmers and crop type, and may include attributes specific to annual crops, contract length, quantity or acreage requirements, quality specifications, payment dates, and other important features. A stated choice survey was administered in three, six-county areas of Kansas by Kansas State University and the USDA, National Agricultural Statistics Service from November 2010 to January 2011 to assess farmers’ willingness to produce cellulosic biomass under different contractual arrangements. This paper focuses on the switchgrass stated choice experiment from the survey. The stated choice experiment asked farmers to rank their preferred contractual arrangement from two contract options and one “do not adopt” option. Contractual attributes included percentage net returns above the next best alternative (e.g. CRP or hay production), contract length, a custom harvest option, insurance availability, and a seed-cost share option. Respondents then ranked their preferred contract option. The survey also collected data on farm characteristics, bioenergy crop preferences, socio-economic demographics, risk preferences, and marketing behavior. The survey used a stratified sample of farmers who farm more than 260 acres and grow corn. A total of 460 surveys were administered with a 65 percent completion rate. The underlying theoretical model uses the random utility model (RUM) approach to assess farmers’ willingness to grow switchgrass for bioenergy and determine the contractual attributes most likely to increase the likelihood of adoption. This framework allows us to define the “price,” or farmers’ mean willingness to accept, for harvested biomass sold to an intermediate processor. The estimated choice models follow the approach of Boxall and Adamowicz (2002) to capture heterogeneity across farmers and geographic regions due to management differences, conservation practices, and risk preferences. Using the percentage net return above CRP or hay production allows prices to float to levels that will entice farmers to adopt switchgrass. This will help determine a market price for bioenergy crops based on current market and production conditions without specifying an exact monetary value for the biomass. In addition, the survey results will facilitate contract designs between biorefineries and farmers while informing policymakers and the biofuel industry about farmers’ willingness to supply biomass for bioenergy production. Reference: Boxall, P.C. and W.L. Adamowicz, “Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach,” Environmental and Resource Economics 23(2002): 421 – 446.Biofuels, Cellulosic, Biomass, Switchgrass, Farmers, Willingness to Pay, Crop Production/Industries, Production Economics, Resource /Energy Economics and Policy,