Transforming AdaPT to Ada

This paper describes how the main features of the proposed Ada language extensions intended to support distribution, and offered as possible solutions for Ada9X can be implemented by transformation into standard Ada83. We start by summarizing the features proposed in a paper (Gargaro et al, 1990) which constitutes the definition of the extensions. For convenience we have called the language in its modified form AdaPT which might be interpreted as Ada with partitions. These features were carefully chosen to provide support for the construction of executable modules for execution in nodes of a network of loosely coupled computers, but flexibly configurable for different network architectures and for recovery following failure, or adapting to mode changes. The intention in their design was to provide extensions which would not impact adversely on the normal use of Ada, and would fit well in style and feel with the existing standard. We begin by summarizing the features introduced in AdaPT

Transforming AdaPT to Ada9x

How the concepts of AdaPT can be transformed into programs using the object oriented features proposed in the preliminary mapping for Ada9x are described. Emphasizing, as they do, the importance of data types as units of program, these features match well with the development of partitions as translations into Abstract Data Types which was exploited in the Ada83 translation covered in report R3. By providing a form of polymorphic type, the Ada83 version also gives support for the conformant partition idea which could be achieved in Ada83 only by using UNCHECKED CONVERSIONS. It is assumed that the reader understands AdaPT itself, but the translation into Ada83 is briefly reviewed, by applying it to a small example. This is then used to show how the same translation would be achieved in the 9x version. It is important to appreciate that the distribution features which are proposed in current mapping are not used or discussed in any detail, as those are not well matched to the AdaPT approach. Critical evaluation and comparison of these approaches is given in a separate report

Languages adapt to their contextual niche

abstractIt is well established that context plays a fundamental role in how we learn and use language. Here we explore how context links short-term language use with the long-term emergence of different types of language system. Using an iterated learning model of cultural transmission, the current study experimentally investigates the role of the communicative situation in which an utterance is produced (situational context) and how it influences the emergence of three types of linguistic systems: underspecified languages (where only some dimensions of meaning are encoded linguistically), holistic systems (lacking systematic structure), and systematic languages (consisting of compound signals encoding both category-level and individuating dimensions of meaning). To do this, we set up a discrimination task in a communication game and manipulated whether the feature dimension shape was relevant or not in discriminating between two referents. The experimental languages gradually evolved to encode information relevant to the task of achieving communicative success, given the situational context in which they are learned and used, resulting in the emergence of different linguistic systems. These results suggest language systems adapt to their contextual niche over iterated learning.</jats:p

Robots that can adapt like animals

As robots leave the controlled environments of factories to autonomously function in more complex, natural environments, they will have to respond to the inevitable fact that they will become damaged. However, while animals can quickly adapt to a wide variety of injuries, current robots cannot "think outside the box" to find a compensatory behavior when damaged: they are limited to their pre-specified self-sensing abilities, can diagnose only anticipated failure modes, and require a pre-programmed contingency plan for every type of potential damage, an impracticality for complex robots. Here we introduce an intelligent trial and error algorithm that allows robots to adapt to damage in less than two minutes, without requiring self-diagnosis or pre-specified contingency plans. Before deployment, a robot exploits a novel algorithm to create a detailed map of the space of high-performing behaviors: This map represents the robot's intuitions about what behaviors it can perform and their value. If the robot is damaged, it uses these intuitions to guide a trial-and-error learning algorithm that conducts intelligent experiments to rapidly discover a compensatory behavior that works in spite of the damage. Experiments reveal successful adaptations for a legged robot injured in five different ways, including damaged, broken, and missing legs, and for a robotic arm with joints broken in 14 different ways. This new technique will enable more robust, effective, autonomous robots, and suggests principles that animals may use to adapt to injury

Decentrilazation as ability to adapt

No abstract availableEconomics ;