Public Benefits of Undeveloped Lands on Urban Outskirts: Non-Market Valuation Studies and their Role in Land Use Plans

Over the past three decades, the economics profession has developed methods for estimating the public benefits of green spaces, providing an opportunity to incorporate such information into land-use planning. While federal regulations routinely require such estimates for major regulations, the extent to which they are used in local land use plans is not clear. This paper reviews the literature on public values for lands on urban outskirts, not just to survey their methods or empirical findings, but to evaluate the role they have played--or have the potential to play-- in actual land use plans. Based on interviews with authors and representatives of funding agencies and local land trusts, it appears that academic work has had a mixed reception in the policy world. Reasons for this include a lack of interest in making academic work accessible to policy makers, emphasizing revealed preference methods which are inconsistent with policy priorities related to nonuse values, and emphasis on benefit-cost analyses. Nevertheless, there are examples of success stories that illustrate how such information can play a vital role in the design of conservation policies. Working Paper 07-2

A probabilistic unified approach for power indices in simple games

The final publication is available at Springer via https://doi.org/10.1007/978-3-662-60555-4_11Many power indices on simple games have been defined trying to measure, under different points of view, the “a priori” importance of a voter in a collective binary voting scenario. A unified probabilistic way to define some of these power indices is considered in this paper. We show that six well-known power indices are obtained under such a probabilistic approach. Moreover, some new power indices can naturally be obtained in this way.Peer ReviewedPostprint (author's final draft

Degeneracy: a link between evolvability, robustness and complexity in biological systems

A full accounting of biological robustness remains elusive; both in terms of the mechanisms by which robustness is achieved and the forces that have caused robustness to grow over evolutionary time. Although its importance to topics such as ecosystem services and resilience is well recognized, the broader relationship between robustness and evolution is only starting to be fully appreciated. A renewed interest in this relationship has been prompted by evidence that mutational robustness can play a positive role in the discovery of adaptive innovations (evolvability) and evidence of an intimate relationship between robustness and complexity in biology. This paper offers a new perspective on the mechanics of evolution and the origins of complexity, robustness, and evolvability. Here we explore the hypothesis that degeneracy, a partial overlap in the functioning of multi-functional components, plays a central role in the evolution and robustness of complex forms. In support of this hypothesis, we present evidence that degeneracy is a fundamental source of robustness, it is intimately tied to multi-scaled complexity, and it establishes conditions that are necessary for system evolvability

Application of Genetic Programming to High Energy Physics Event Selection

We review genetic programming principles, their application to FOCUS data samples, and use the method to study the doubly Cabibbo suppressed decay D+ -> K+ pi+ pi- relative to its Cabibbo favored counterpart, D+ -> K- pi+ pi+. We find that this technique is able to improve upon more traditional analysis methods. To our knowledge, this is the first application of the genetic programming technique to High Energy Physics data.Comment: 39 page

Landscape Encodings Enhance Optimization

Hard combinatorial optimization problems deal with the search for the minimum cost solutions (ground states) of discrete systems under strong constraints. A transformation of state variables may enhance computational tractability. It has been argued that these state encodings are to be chosen invertible to retain the original size of the state space. Here we show how redundant non-invertible encodings enhance optimization by enriching the density of low-energy states. In addition, smooth landscapes may be established on encoded state spaces to guide local search dynamics towards the ground state