This article reviews, and rethinks, a few leading themes of the biolinguistic program since its inception in the early 1950s, at each stage influenced by developments in the biological sciences. The following also discusses how the questions now entering the research agenda develop in a natural

Abstract. Given a set of processes and a set of tests on these processes we show how to define in a natural way three different eyuitalences on processes. ThesP equivalences are applied to a particular language CCS. We give associated complete proof systems and fully abstract models. These models

The classical model of visual processing in cortex is a hierarchy of increasingly sophisticated representations, extending in a natural way the model of simple to complex cells of Hubel and Wiesel. Somewhat surprisingly, little quantitative modeling has been done in the last 15 years to explore

result in classification performance superior to that of the model based approaches. An ideal classifier should combine these two complementary approaches. In this paper, we develop a natural way of achieving this combination by deriving kernel functions for use in discriminative methods such as support

r, w, and the file's voting configuration. The algorithm guarantees serial consistency, admits temporary copies in a natural way by the introduction of copies of an application system called Violet.

The goal of this work is to accurately detect and localize boundaries in natural scenes using local image measurements. We formulate features that respond to characteristic changes in brightness, color, and texture associated with natural boundaries. In order to combine the information from

) are dropped, then the natural physical dynamics of the hardware can be exploited in new ways. The notion of an artificially evolving `species' (SAGA) allows the open-ended incremental evolution of complex circuits. Theoretical arguments are given, as well as the real-world example of an evolved hardware

intrusions involving sendmail and lpr. This work is part of a research program aimed at building computer security systems that incorporate the mechanisms and algorithms used by natural immune systems. 1 Introduction We are interested in developing computer security methods that are based on the way natural

Context-enabled applications are just emerging and promise richer interaction by taking environmental context into account. However, they are difficult to build due to their distributed nature and the use of unconventional sensors. The concepts of toolkits and widget libraries in graphical user

and action to be included in the reinforcement learning framework in a natural and general way. In particular, we show that options may be used interchangeably with primitive actions in planning methods such as dynamic programming and in learning methods such as Q-learning. Formally, a set of options defined