An Introduction to MultiAgent Systems.

List of Contributors Preface 1. Introduction K.V. Madhava Rao.- 2.Water Stress A. Yokota, K. Takahara and K. Akashi.- 3.Salt Stress Zora Dajic .- 4. High Temperature Stress Thomas D. Sharkey and Stephen M. Schrader.- 5. Freezing Stress Russell G. Trischuk, Brian S. Schilling, M. Wisniewski and Lawrence V. Gusta .- 6.Photooxidative Stress Attipalli R. Reddy and Agepati S. Raghavendra.- 7.Nutrient Stress K. Janardhan Reddy.- 8.Heavy Metal Stress Ksenija Gasic and Schuyler S. Korban.- 9.Metabolic Engineering for Stress Tolerance Bala Rathinasabapathi and Ramandeep Kaur.- 10.Functional Genomics of Stress Tolerance Akhilesh K. Tyagi, Shubha Vij and Navinder Saini.- Index

Physiology and molecular biology of stress tolerance in plants

Boron-induced oxidative damage and antioxidant and nucleolytic responses in shoot tips culture of the apple rootstock EM 9 (Malus domestica Borkh)

This article evaluates features of leaf and flower senescence that are shared with, or are different from, those of other terminal events in plant development. Alterations of plastid structure and function in senescence are often reversible and it is argued that such changes represent a process of transdifferentiation or metaplasia rather than deterioration. It may be that the irreversible senescence of many flowers and some leaves represents the loss of ancestral plasticity during evolution. Reversibility serves to distinguish senescence fundamentally from programmed cell death (PCD), as does the fact that viability is essential for the initiation and progress of cell senescence. Senescence (particularly its timing and location) requires new gene transcription, but the syndrome is also subject to significant post- transcriptional and post-translational regulation. The reversibility of senescence must relate to the plastic, facultative nature of underlying molecular controls. Senescence appears to be cell-autonomous, though definitive evidence is required to substantiate this. The vacuole plays at least three key roles in the development of senescing cells: it defends the cell against biotic and abiotic damage, thus preserving viability, it accumulates metabolites with other functions, such as animal attractants, and it terminates senescence by becoming autolytic and facilitating true cell death. The mechanisms of PCD in plants bear a certain relation to those of apoptosis, and some processes, such as nucleic acid degradation, are superficially similar to aspects of the senescence syndrome. It is concluded that, in terms of physiological components and their controls, senescence and PCD are at best only distantly related.

Defining senescence and death

Everyone knows and seems to agree that melanocytes are there to generate melanin - an intriguing, but underestimated multipurpose molecule that is capable of doing far more than providing pigment and UV protection to skin (1). What about the cell that generates melanin, then? Is this dendritic, neural crest-derived cell still serving useful (or even important) functions when no-one looks at the pigmentation of our skin and its appendages and when there is essentially no UV exposure? In other words, what do epidermal and hair follicle melanocytes do in their spare time - at night, under your bedcover? How much of the full portfolio of physiological melanocyte functions in mammalian skin has really been elucidated already? Does the presence or absence of melanocytes matter for normal epidermal and/or hair follicle functions (beyond pigmentation and UV protection), and for skin immune responses? Do melanocytes even deserve as much credit for UV protection as conventional wisdom attributes to them? In which interactions do these promiscuous cells engage with their immediate epithelial environment and who is controlling whom? What lessons might be distilled from looking at lower vertebrate melanophores and at extracutaneous melanocytes in the endeavour to reveal the 'secret identity' of melanocytes? The current Controversies feature explores these far too infrequently posed, biologically and clinically important questions. Complementing a companion viewpoint essay on malignant melanocytes (2), this critical re-examination of melanocyte biology provides a cornucopia of old, but under-appreciated concepts and novel ideas on the slowly emerging complexity of physiological melanocyte functions, and delineates important, thought-provoking questions that remain to be definitively answered by future research.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1600-0625.2009.00912.x

What are melanocytes really doing all day long

The implementation process of complex agent and multi-agent systems (AMAS) can benefit significantly from a simulation platform that would allow rapid prototyping and testing of initial design ideas and choices. Such a platform, should ideally have a small learning curve, easy implementation and visualisation of the AMAS under development, while preserving agent oriented programming characteristics that would allow to easily port the design choices to a fully-fledged agent development environment. However, these requirements make such a simulation platform an ideal learning tool as well. We argue that NetLogo meets most of the requirements that suit our criteria. In addition, we describe two extra NetLogo libraries, one for BDI-like agents and one for ACL-like communication that allow effortless development of goal-oriented agents, that communicate using FIPA-ACL messages. We present one simulation scenario that employs these libraries to provide an implementation in which agents cooperate under a Contract Net protocol.

/pdf/enhancing-netlogo-to-simulate-bdi-communicating-agents-qdpiprjnc0.pdf

Enhancing NetLogo to Simulate BDI Communicating Agents

One of the most essential phases of software development is the system specification. Xmachines is an intuitive formal method which can be easily applied at this phase and also facilitate testing in order to prove the correctness of an implementation with respect to the specification. Although the X-Machine theory is already defined in detail mathematically, there is a lack of automated tools which can facilitate its use. In this paper, a brief introduction to the X-Machine theory is presented and a language for specifying X-Machines is defined, which could act as a communication protocol among various X-Machine tools. In addition, a proof tool is presented which checks special properties of X-Machines that are defined as prerequisites for the X-Machine testing algorithm.

A design language and tool for x-machines specification

Recent advances in testing and verification of software based on formal specifications of the system to be built have reached a point where the ideas can be applied in a powerful way in the design of agent-based systems. The software engineering research has highlighted a number of important issues: the importance of the type of modeling technique used; the careful design of the model to enable powerful testing techniques to be used; the automated verification of the behavioral properties of the system; and the need to provide a mechanism for translating the formal models into executable software in a simple and transparent way. This chapter presents a detailed and comprehensive account of the ways in which some modern software engineering research can be applied 701 E. Chocolate Avenue, Hershey PA 17033-1240, USA Tel: 717/533-8845; Fax 717/533-8661; URL-http://www.idea-group.com ITB8743 IDEA GROUP PUBLISHING This chapter appears in the book, Intelligent Agent Software Engineering, edited by Valentina Plekhanova. Copyright © 2003, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. A Formal Method for Development of Agent-Based Systems 69 Copyright © 2003, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Copyrigh t Idea Gro up Inc. Copy right Idea Grou p Inc . opyri ght Id ea G roup Inc. Copy right Idea Grou p Inc . to the construction of effective and reliable agent-based software systems. More specifically, we intend to show how simple agents motivated from biology can be modeled as X-machines. Such modeling will facilitate verification and testing of an agent model, because appropriate strategies for model checking and testing are already developed around the Xmachine method. In addition, modular construction of agent models is feasible, because X-machines are provided with communicating features, which allow simple models to interact. INTRODUCTION An agent is an encapsulated computer system situated in some environment that is capable of flexible, autonomous action in that environment in order to meet its design objectives (Jennings, 2000). There are two fundamental concepts associated with any dynamic or reactive system, such as an agent, that is situated in and reacting with some environment (Holcombe & Ipate, 1998):  The environment, which could be precisely or ill-specified or even completely unknown, but nevertheless, involves identifying the important aspects of the environment and the way in which they may change in accordance with the activities of the agent  The agent will be responding to environmental changes by changing its basic parameters and possibly affecting the environment as well. Thus, there are two ways in which the agent reacts, i.e., it undergoes internal changes, and it produces outputs that affect the environment Agents, as highly dynamic systems, are concerned with three essential factors:  A set of appropriate environmental stimuli or inputs  A set of internal states of the agent  A rule that relates the two above and determines what the agent state will change to if a particular input arrives while the agent is in a particular state One of the challenges that emerges in intelligent agent engineering is to develop agent models and agent implementations that are correct. According to Holcombe and Ipate (1998), the criteria for correctness are as follows:  The initial agent model should match with the requirements  The agent model should satisfy any necessary properties in order to meet its design objectives 29 more pages are available in the full version of this document, which may be purchased using the "Add to Cart" button on the publisher's webpage: www.igi-global.com/chapter/formal-method-developmentagent-based/24145

A Formal Method for the Development of Agent-Based Systems

In this paper the behaviour of a bee colony is modelled as society of communicating agents acting in parallel and synchronising their behaviour. Two computational approaches for defining the agents behaviour are introduced and compared. Their common features as well as the complementary aspects making them suitable for merging together into a more complex model.

Computational models of collective foraging

An X-machine is a general computational machine that can model: (a) non-trivial data structures as a typed memory tuple and (b) the dynamic part of a system by employing transitions, which are not labelled with simple inputs but with functions that operate on inputs and memory values. The X-machine formal method is valuable to software engineers since it is rather intuitive, while at the same time formal descriptions of data types and functions can be written in any known mathematical notation. These differences allow the X-machines to be more expressive and flexible than a Finite State Machine. In addition, a set of X-machines can be viewed as components, which communicate with each other in order to specify larger systems. This paper describes a methodology as well as an appropriate notation, namely X-machine Description Language (XMDL), for building communicating X-machines from existing stand-alone X-machine models. The proposed methodology is accompanied by an example model of a traffic light junction, which demonstrates the use of communicating X-machines towards the incremental modelling of large-scale systems. It is suggested that through XMDL, the practical development of such complex systems can be split into two separate activities: (a) the modelling of stand-alone X-machine components and (b) the description of the communication between these components. The approach is disciplined, practical, modular and general in the sense that it subsumes the existing methods for communicating X-machines.

Petros Kefalas

Papers

Enhancing NetLogo to Simulate BDI Communicating Agents

A design language and tool for x-machines specification

A Formal Method for the Development of Agent-Based Systems

Computational models of collective foraging

Communicating X-machines: a practical approach for formal and modular specification of large systems