A Complex System (CS) exhibits the four salient properties: (i) Collective, coordinated and efficient interaction among its components (ii) Self-organization and emergence (iii) Power law scaling under emergence (iv) Adaptation, fault tolerance and resilience against damage of its components. We describe briefly, three interrelated mathematical models that enable us to understand these properties: Fractal and percolation model, Stochastic / Chaotic (nonlinear) dynamical model and Topological (network) or graph model. These models have been very well studied in recent years and are closely related to the properties such as: self-similarity, scale-free, resilience, self-organization and emergence. We explain how these properties of CS can be simulated using the multi-set of agents-based paradigm (MAP) through random enabling, inhibiting, preferential attachment and growth of the multiagent network. We discuss these aspects from the point of view of geometric parameters-Lyapunov exponents, strange attractors, metric entropy, and topological indices-Cluster coefficient, Average degree distribution and the correlation length of the interacting network. We also describe the advantages of agent-based modelling, simulation and animation. These are illustrated by a few examples in swarm dynamics- ant colony, bacterial colonies, human-animal trails, and graph-growth. We briefly consider the engineering of CS, the role of scales, and the limitations arising from quantum mechanics. A brief summary of currently available agent-tool kits is provided. Further developments of agent technology will be of great value to model, simulate and animate, many phenomena in Systems biology-cellular dynamics, cell motility, growth and development biology (Morphogenesis), and can provide for improved capability in complex systems modelling.

A cooperating-agents sensor based algorithm is described to detect temporal consistency among events and for constraint processing. We describe the algorithm using an example. Also we describe the cooperative aspects of the agent -based algorithm using an UML activity diagram.

An interacting multi-agent system in a network can model the evolution of a Nature-Inspired Smart System (NISS) exhibiting the four salient properties: (i) Collective, coordinated and efficient (ii) Self-organization and emergence (iii) Power law scaling or scale invariance under emergence (iv) Adaptive, fault tolerant and resilient against damage. We explain how these basic properties can arise among agents through random enabling, inhibiting, preferential attachment and growth of a multiagent system. The quantitative understanding of a Smart system with an arbitrary interactive topology is extremely difficult. However, for specific applications and a pre-defined static interactive topology among the agents, the quantitative parameters can be obtained through simulation to build a specific NISS. Further developments of agent technology will be of great value to model, simulate and animate, many phenomena in Systems biology - pattern formation, cellular dynamics, cell motility, growth and development biology, and can provide for improved capability in complex systems modelling. Also agents will serve as useful tools to model, design and develop biomorphic robots and neuromorphic chips.

An interacting multi-agent system in a network can behave like a nature-inspired smart system (SS) exhibiting the four salient properties of an artificial life system (ALS): (i) Collective, coordinated and efficient (ii) Self-organization and emergence (iii) Power law scaling or scale invariance under emergence (iv) Adaptive, fault tolerant and resilient against damage. We explain how these basic properties can arise among agents through random enabling, inhibiting, preferential attachment and growth of a multiagent system. However,the quantitative understanding of a Smart system with an arbitrary interactive topology is extremely difficult. Hence we cannot design a general purpose programmable Smart system. However, for specific applications and a predefined static interactive topology among the agents, the quantitative parameters can be obtained through simulation to build a specific SS.

This chapter describes the system design for a multimedia telediagnostic computing environment (MMTE) for telemedical applications. Such an environment requires the design of: (i) a wired-in or wireless computing facility based on currently available technology with a high bandwidth for fast, reliable, and efficient communication of data, voice, and image; (ii) a database query system to access data, voice, and medical images from a fixed server to the mobile or fixed hosts; and (iii) suitable audiovisual software communication tools among the cooperating fixed and mobile hosts to help visualize pointer movements remotely (telepointers) and for teleconferencing. Appropriate software and hardware tools for the design of the cooperative environment are described. We also provide an up-to-date bibliography.

A multiset of agents can mimic the evolution of the nature-inspired computations, e.g., genetic, self-organized criticality and active walker (swarm and ant intelligence) models. Since the reaction rules are inherently parallel, any number of actions can be performed cooperatively or competitively among the subsets of the agents, so that the system evolve reaches an equilibrium, a chaotic or a self-organized emergent state. Examples of natural evolution , including wasp nest construction through a probabilistic shape-grammar are provided.

This chapter describes an object-based workflow paradigm to support long and short duration transactions in a mobile e-commerce (or m-commerce) environment. In the mobile computing environment, the traditional transaction model needs to be replaced by a more realistic model (called a “workflow model”) between several clients and servers that interact, compete, and cooperate, realising an intergalactic client-server program (ICSP). The various types of task patterns that arise in m-commerce (e-checking, shipping goods, purchasing, and market forecasting) require a subjunctive, or “what-if,” programming approach, consisting of intention and actions for trial-error design, before an actual commitment is made. Eiffel, iContract tool of Java, and UML are powerful languages to implement the intergalactic client-server program (ICSP). They provide for a software contract that captures mutual obligations through program constructs to take care of the unpredictable nature of connectivity of the mobile devices and the networks, as well as the trial and error program design required in m-commerce.

This article describes in brief the design of agent-based negotiation system in e-marketing. Such a negotiation scheme requires the construction of a suitable set of rules, called protocol, among the participating agents. The construction of the protocol is carried out in two stages: first expressing a program into an object-based rule system and then converting the rule applications into a set of agent-based transactions on a database of active objects represented using high-level data structures.

We describe how a set of agents can collaborate in E-marketing- in particular, we consider E- Auction. We also give a theoretical basis to detect the collaboration termination, without indefinite cycling, We also discus the possibility of self-organized criticality among interacting agents in which there is stochastic emergence of collective knowledge due to agent's internal reasoning, as well as, incremental knowledge obtained from interactions with other agents.

A smart system exhibits the four important properties: (i) Interactive, Collective, coordinated and Parallel Operation (ii) Self-organization through emergent properties (iii) Power law scaling under emergence (iv) Adaptive and Flexible operation. We describe the role of fractal and percolation model for understanding smart systems. A hierarchy based on metric entropy is suggested among the computational systems that transcend from the unsmart to the smart system through a phase transition like phenomenon. Understanding smart systems is useful to solve hard-optimization problem inspired by the self-organizing processes found in nature.

This paper describes how a set of agents can be used for collaboration in E-marketing and E-Auction. We have formalized an integrated model consisting of the salient features of several agent paradigms, and link it with the distributed software engineering methodology. The integrated model proposed here has the simplicity and adaptability for realisation as a distributed transaction-based paradigm for negotiation and other E-marketing problems. Also it can provide an insight into the self-organized criticality in a network of agents.

This chapter describes the Operational Models, Programming Paradigms and Software Tools needed for building a Web- integrated network computing environment. We describe the various interactive distributed computing models (client server-CS, code on demand, remote evaluation, mobile agents, three and N-tier system), different logical modes of programming (imperative, declarative, subjunctive, and abductive), transaction and workflow models (that relax atomicity, consistency, isolation, durability and serializability properties), new protocols, and software tools (PJava/JDBC) that are needed. Some important application areas of these models are for telediagnosis and cooperative problem solving.

Scalable performance can be obtained in a network cluster of workstations by proper choice of programming paradigm and software tools such as PVM/MPI. However, the ratio of message transmission time to computation time plays a crucial role. For regular problems such as matrix computations this ratio can be easily inferred. However, for more complex problems such as evolutionary computations this ratio cannot be arrived at unless the programmer has very good problem domain knowledge.

We propose a multi-agent transactional paradigm based on object-based rule systems for realising distributed agent negotiation protocols in E-marketing. The construction of the protocol is carried out in two stages: first expressing a program into an object-based rule system and then converting the rule applications into a set of transactions on a database of active objects. Also, an algorithm to prove termination of the negotiation among the agents is described.

While using a cluster of computers in a network environment several issues need to be considered: (i) choice of models for software architectural pattern, (ii) program serializability, fault tolerance and recovery, (iii) choice of programming paradigms, (iv) factors affecting scalability in performance-such as transmission and computation times, (v) dangers of cumulative errors, (vi) compatibility and interoperability. The paper describes some basic models for cluster computing. Also it considers the issues of global serializability and scalability and provides some useful insights on the evolution of new practical software tools.

An agent based paradigm is proposed for mobile computing. The fixed host deploys an agent in the mobile host that is provided with a rule or event-condition-based power of attorney, to act on its behalf. The rule application policy enforces that the transactions are either time and attribute sensitive or time and attribute tolerant. Issues related to rule compatibility, cache consistency, recovery and mobile-host dependencies are considered. Also we consider the relaxation of ACID and serializability properties of transactions in a mobile computing environment.

This paper presents an overview of the Models, Programming Paradigms and Software Tools needed for an integrated network (wired and wireless) computing environment that can support electronic Commerce. In particular we consider the role of various interactive distributed computing models (client server-CS, code on demand -COD, remote evaluation- REV, and mobile agents - MA, and three-tier system- TTS), different logical modes of programming (Imperative, declarative, subjunctive and abductive), transaction and workflow models (that relax atomicity, consistency, isolation, duarbility and serializability properties), new protocols and software tools (PJava/JDBC/CORBA products) that are needed.

A new multiagent programming paradigm based on the transactional logic model is developed. This paradigm enables us to construct a distributed agent transactional program (DATRAP). Such a construction is carried out in two stages: first expressing a program into a production rule system, and then converting the rule applications into a set of transactions on a database of active objects represented using high-level data structures. The formal specification and refinement calculus are key features in the development of a DATRAP. We also indicate how to specify granularity of parallelism and also achieve several types of parallelism. One can associate with a DATRAP two different types of execution semantics called set-based and instance-based semantics. We also show how to prove correctness of DATRAP, achieve maximal concurrence and reduce the complexity of a distributed program

A transactional paradigm is suggested for computer-assisted parallelization of programs and register-cache scheduling. It can serve as a building tool for pipelining, data parallellism, or generic parallellism in a variety of architectures and the cost of execution can be estimated realistically.<>