Despite the plethora of frameworks and tools for developing agent systems, there is a remarkable lack of generalized methodologies for assessing their performance, while adequately addressing the unpredictable and complex nature of intelligent agents. In this paper, we present a generic methodology for evaluating agent performance, the Agent Performance Evaluation (APE) methodology that consist...

Let G = GSp(2) be the symplectic group with similitude of degree two, which is defined over Q. For a generic cusp form F on the adelized group GA which generates a large discrete series representation at infinity, we show that its spinor Lfunction is continued to an entire function and satisfies the functional equation. 0. Introduction. Let G = GSp(2) be the symplectic group with similitude of ...

Java generics, found in versions 1.5 and later, are implemented by generating only one byte code representation of a generic type or method; a compiler maps all the instantiations of a generic type or method to that unique representation via type erasure. The essence of type erasure is the removal during compilation of all information that is related to type parameters and type arguments. From ...

Large, pre-trained language models (PLMs) such as BERT and GPT have drastically changed the Natural Language Processing (NLP) field. For numerous NLP tasks, approaches leveraging PLMs achieved state-of-the-art performance. The key idea is to learn a generic, latent representation of from generic task once, then share it across disparate tasks. modeling serves task, one with abundant self-superv...

A discrete-logarithm algorithm is called generic if it does not exploit the specific representation of the cyclic group for which it is supposed to compute discrete logarithms. Such algorithms include the well-known Baby-Step-Giant-Step procedure as well as the PohligHellman algorithm. In particular, these algorithms match a lower bound of Nachaev showing that generic discrete-log algorithms re...

As part of the StAR project, for the design of a computer system to support risk assessment, it has been necessary to develop a graphical language for the representation of generic structures. These structures are used by rule writers to describe toxicophores for risk assessment. Until now, the input of generic structures in knowledge-based systems has very often been by means of a SMILES-like ...

Many visual datasets are traditionally used to analyze the performance of different learning techniques. The evaluation is usually done within each dataset, therefore it is questionable if such results are a reliable indicator of true generalization ability. We propose here an algorithm to exploit the existing data resources when learning on a new multiclass problem. Our main idea is to identif...

Despite the plethora of frameworks and tools for developing agent systems, there is a remarkable lack of generalised methodologies for assessing their performance. Existing methods in the field of software engineering do not adequately address the unpredictable and complex nature of intelligent agents. We introduce a generic methodology for evaluating agent performance; the Agent Performance Ev...

Based on a review of existing standards and guidelines as well as the current international practice of modeling measurement units and related concepts in representation of economic and statistical data, a generic data model for statistical indicators and measurement units is introduced that may contribute to the further development of the SDMX content oriented guidelines in terms of harmonizin...

Liquid Haskell augments the Haskell language with theorem proving capabilities, allowing programmers to express and prove class laws. But many of these proofs require routine, boilerplate code and do not scale well, as the size of proof terms can grow superlinearlywith the size of the datatypes involved in the proofs. We present a technique to derive Haskell proof terms by leveraging datatype-g...