Originally, behavioral law and economics was an exercise in exploring the implications of key findings from behavioral economics (and psychology) for the analysis and reform of legal institutions. Yet as the new discipline matures, it increasingly replaces foreign evidence by fresh evidence, directly targeted to the legal research question. This chapter surveys the key methods: field evidence, ...

Traditional dimensional analysis techniques for predicting the performance characteristics of a product can be greatly improved in both accuracy and domain of applicability by the infusion of empirical data, derived from material tests, into the equations that characterize the system parameters of interest. Advanced similarity methods are investigated which overcome the constraints associated w...

OF THE DISSERTATION IMPROVED EMPIRICAL METHODS IN REINFORCEMENT-LEARNING EVALUATION by VUKOSI N. MARIVATE Dissertation Director: Michael L. Littman The central question addressed in this research is ”can we define evaluation methodologies that encourage reinforcement-learning (RL) algorithms to work effectively with real-life data?” First, we address the problem of overfitting. RL algorithms ar...

We claim that the methods used in approaches to discourse all display in rather acute form the gap between theory and evidence that is common in many areas of cognitive science. We propose enhancing the existing approaches with a simulation-based approach combining computational work in generation and interpretation, and discuss some of the issues in the design of a simulation architecture.

Many machine learning and neurally inspired algorithms are limited, at least in their pure form, to working with nominal data. However, for many real-world problems, some provision must be made to support processing of continuously valued data. This paper presents empirical results obtained by using six different discretization methods as preprocessors to three different supervised learners on ...

In this paper we present a comprehensive comparison of the performance of a number of text categorization methods in two different data sets. In particular, we evaluate the Vector and Latent Semantic Analysis (LSA) methods, a classifier based on Support Vector Machines (SVM) and the k-Nearest Neighbor variations of the Vector and LSA models. We report the results obtained using the Mean Recipro...

Ockham’s razor is the principle that, all other things being equal, scientists ought to prefer simpler theories. In recent years, philosophers have argued that simpler theories make better predictions, possess theoretical virtues like explanatory power, and have other pragmatic virtues like computational tractability. However, such arguments fail to explain how and why a preference for simplici...

Online Social Networks are growing exponentially due to which a lot of researchers are working on Social Network analysis. Link Prediction is a task of predicting new links that may occur in future in the social network. The link prediction problem has generated a lot of interest due its widespread applicability across many domains. We conducted a study on the different methods that have been d...

One of the major interests in extreme-value statistics is to infer the tail properties of the distribution functions in the domain of attraction of an extreme-value distribution and to predict rare events. In recent years, much effort in developing new methodologies has been made by many researchers in this area so as to diminish the impact of the bias in the estimation and achieve some asympto...

Parallel translations of written texts have long been useful tools for human students of language, and have begun to serve as an intriguing source of data for corpus-based approaches to natural language processing. A source text and its translation can be viewed as a coarse map between the two languages, and an industrious student or clever computer program may wish to refine that mapping so th...