Learning more effectively from experience

Developing the capacity for individuals to learn effectively from their experiences is an important part of building the knowledge and skills in organizations to do good adaptive management. This paper reviews some of the research from cognitive psychology and phenomenography to present a way of thinking about learning to assist individuals to make better use of their personal experiences to develop understanding of environmental systems. We suggest that adaptive expertise (an individual’s ability to deal flexibly with new situations) is particularly relevant for environmental researchers and practitioners. To develop adaptive expertise, individuals need to: (1) vary and reflect on their experiences and become adept at seeking out and taking different perspectives; and (2) become proficient at making balanced judgements about how or if an experience will change their current perspective or working representation of a social, economic, and biophysical system by applying principles of “good thinking.” Such principles include those that assist individuals to be open to the possibility of changing their current way of thinking (e.g., the disposition to be adventurous) and those that reduce the likelihood of making erroneous interpretations (e.g., the disposition to be intellectually careful). An example of applying some of the principles to assist individuals develop their understanding of a dynamically complex wetland system (the Macquarie Marshes in Australia) is provided. The broader implications of individual learning are also discussed in relation to organizational learning, the role of experiential knowledge for conservation, and for achieving greater awareness of the need for ecologically sustainable activity

An Extensible Benchmarking Infrastructure for Motion Planning Algorithms

Sampling-based planning algorithms are the most common probabilistically complete algorithms and are widely used on many robot platforms. Within this class of algorithms, many variants have been proposed over the last 20 years, yet there is still no characterization of which algorithms are well-suited for which classes of problems. This has motivated us to develop a benchmarking infrastructure for motion planning algorithms. It consists of three main components. First, we have created an extensive benchmarking software framework that is included with the Open Motion Planning Library (OMPL), a C++ library that contains implementations of many sampling-based algorithms. Second, we have defined extensible formats for storing benchmark results. The formats are fairly straightforward so that other planning libraries could easily produce compatible output. Finally, we have created an interactive, versatile visualization tool for compact presentation of collected benchmark data. The tool and underlying database facilitate the analysis of performance across benchmark problems and planners.Comment: Submitted to IEEE Robotics & Automation Magazine (Special Issue on Replicable and Measurable Robotics Research), 201

Q-based design equations for resonant metamaterials and experimental validation

Practical design parameters of resonant metamaterials, such as loss tangent, are derived in terms of the quality factor $Q$ of the resonant effective medium permeability or permittivity. Through electromagnetic simulations of loop-based resonant particles, it is also shown that the $Q$ of the effective medium response is essentially equal to the $Q$ of an individual resonant particle. Thus, by measuring the $Q$ of a single fabricated metamaterial particle, the effective permeability or permittivity of a metamaterial can be calculated simply and accurately without requiring complex simulations, fabrication, or measurements. Experimental validation shows that the complex permeability analytically estimated from the measured $Q$ of a single fabricated self-resonant loop agrees with the complex permeability extracted from $S$ parameter measurements of a metamaterial slab to better than 20%. This $Q$ equivalence reduces the design of a metamaterial to meet a given loss constraint to the simpler problem of the design of a resonant particle to meet a specific $Q$ constraint. This analysis also yields simple analytical expressions for estimating the loss tangent of a planar loop magnetic metamaterial due to ohmic losses. It is shown that $\tan \delta \approx 0.001$ is a strong lower bound for magnetic loss tangents for frequencies not too far from 1 GHz. The ohmic loss of the metamaterial varies inversely with the electrical size of the metamaterial particle, indicating that there is a loss penalty for reducing the particle size at a fixed frequency

Rigidity around Poisson Submanifolds

We prove a rigidity theorem in Poisson geometry around compact Poisson submanifolds, using the Nash-Moser fast convergence method. In the case of one-point submanifolds (fixed points), this immediately implies a stronger version of Conn's linearization theorem, also proving that Conn's theorem is, indeed, just a manifestation of a rigidity phenomenon; similarly, in the case of arbitrary symplectic leaves, it gives a stronger version of the local normal form theorem; another interesting case corresponds to spheres inside duals of compact semisimple Lie algebras, our result can be used to fully compute the resulting Poisson moduli space.Comment: 43 pages, v3: published versio

Weakly Picard mappings

summary:In this paper we generalize the well known converse to the contraction principle due to C. Bessaga, dropping the uniqueness of the fixed point from its hypotheses. Some properties of weakly Picard mappings are given