The Purdue PSE Kernel: Towards a kernel for building PSEs

Abstract Problem Solvillg Environments (PSEs

An agent-based approach to building multidisciplinary problem-solving environments

Electronic prototyping is becoming a part of every scientific inquiry and product design. The rapid prototyping of manufactured artifacts and the rapid solution of problems with numerous interrelated elements requires the fast, accurate simulation of physical processes using knowledge and computational models from multiple disciplines in science and engineering. We argue the necessity of a generally applicable and flexible programming environment for simulating (numerically) multiple-domain, heterogeneous, and possibly very complex multiphysics phenomena that is accessible to users who are not experts in scientific computing. We argue that one can be built with the extensive use of available legacy simulation software. We present a paradigm for simulating such complex models that may involve multiple physical phenomena and complicated geometry. The computational structure is of cooperating agents, and much of the proposed methodology is widely applicable; but the focus in this work is on phenomena modeled by partial differential equations (PDEs). The computational process is to subdivide the physical object into components of simple geometric shapes each modeled by a single problem solving environment (PSE). PSEs are viewed as agents that solve PDEs on each component independently. The interfaces between the components must have physical interface conditions satisfied--mediator agents use relaxation techniques for this. An agent-based architecture of an environment for building systems to implement this paradigm, along with the necessary mathematical and software tools for building it, are described, using PSEs that are encapsulated and transformed into solver agents. This approach is naturally parallel and highly scalable; it is suitable for a wide variety of parallel and distributed high performance computing (HPC) architectures; it is easily applicable in the context of networked and network-centric computing; it allows for the reuse and evolution of existing HPC software and for a convenient abstraction of the solution process and the low cost building of the simulation software for non-expert users. An implementation of the architecture, named SciAgents, is presented which illustrates this multidisciplinary problem solving environments (MPSE) framework. The detailed software architecture and the prototype implementation of SciAgents are discussed in the context of a set of examples

SciAgents--An Agent Based Environment for Distributed, Cooperative Scientific Computing

Problem solving using complex mathematical models of the physical phenomena requires expert knowledge in a variety of fields of computer science, such as parallel computing and numerical methods. This often makes application scientists, who have the domain expertise to devise the mathematical models, unable to use the power of High Performance Computing (HPC) systems. SciAgents is a problem solving environment to allow these models and systems to become truly easy to use for the application scientists, much like PC-based systems. It is based on the agent-oriented model of computing. In this paper, we discuss the design and architecture of SciAgents. We present a set of artificial/computational intelligence techniques used by the cooperating agents that constitute SciAgents , which allows them to complete the program specification and to carry out the program execution with minimal need for user intervention. We describe the design in context of scientific computing models based on par..

An Agent-Based Approach to Building Multidisciplinary Problem Solving Environments

Electronic prototyping is becoming a part of every scientific inquiry and product design. The rapid prototyping of manufactured artifacts and the rapid solution of problems with numerous interrelated elements requires the fast, accurate simulation of physical processes using knowledge and computational models from multiple disciplines in science and engineering. We argue the necessity of a generally applicable and flexible programming environment for simulating (numerically) multiple-domain, heterogeneous, and possibly very complex multiphysics phenomena that is accessible to users who are not experts in scientific computing. We argue that one can be built with the extensive use of available legacy simulation software. We present a paradigm for simulating such complex models that may involve multiple physical phenomena and complicated geometry. The computational structure is of cooperating agents, and much of the proposed methodology is widely applicable; but the focus in this work is on phenomena modeled by partial differential equations (PDEs). The computational process is to subdivide the physical object into components of simple geometric shapes each modeled by a single problem solving environment (PSE). PSEs are viewed as agents that solve PDEs on each component independently. The interfaces between the components must have physical interface conditions satisfied--mediator agents use relaxation techniques for this. An agent-based architecture of an environment for building systems to implement this paradigm, along with the necessary mathematical and software tools for building it, are described, using PSEs that are encapsulated and transformed into solver agents. This approach is naturally parallel and highly scalable; it is suitable for a wide variety of parallel and distributed high performance computing (HPC) architectures; it is easily applicable in the context of networked and network-centric computing; it allows for the reuse and evolution of existing HPC software and for a convenient abstraction of the solution process and the low cost building of the simulation software for non-expert users. An implementation of the architecture, named SciAgents, is presented which illustrates this multidisciplinary problem solving environments (MPSE) framework. The detailed software architecture and the prototype implementation of SciAgents are discussed in the context of a set of examples

A Software Architecture Of Collaborating Agents For Solving PDEs

: : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : vii 1. INTRODUCTION : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 1 1.1 Solving PDE Problems : : : : : : : : : : : : : : : : : : : : : : : : : : 1 1.1.1 Solvers for Simple PDE Problems : : : : : : : : : : : : : : : : 1 1.1.2 Multiple-domain PDE Problems : : : : : : : : : : : : : : : : : 3 1.1.3 Interface Conditions and Their Processing : : : : : : : : : : : 7 1.1.4 Interface Relaxation Technique : : : : : : : : : : : : : : : : : 8 1.1.5 Software Reuse Problem : : : : : : : : : : : : : : : : : : : : : 11 1.2 Agent-based Computing Paradigm : : : : : : : : : : : : : : : : : : : 12 1.2.1 The Concept of an Agent : : : : : : : : : : : : : : : : : : : : 12 1.2.2 KQML --- A Standard for Exchanging Information (Knowledge) between Agents : : : : : : : : : : : : : : : : : : : : : : : : : : 14 1.2.3 Visual Programming Languages and User Interfaces : : : : : : 15 2. SOME ISSUES IN INTERFACE RELAXATION AND DOMAIN..

Science Pad: An Intelligent Electronic Notepad for Ubiquitous Scientific Computing

The National Information Infrastructure (NII) that will evolve in the 1990's and beyond will impact many institutions of life. These include the way we learn and do science, self-caring, access to civil/information infrastructure systems & services, and management & control of manufacturing processes. The future scenario for the NII assumes wireless networks used by walkstations realizing the dream of truly ubiquitous access to the information superhighway. Some of the current obstacles in building such a ubiquitous access system on mobile high-performance platforms include the user interface for these walkstations, the ability of sniffing information across heterogeneous geographically distributed information systems, the ability of processing sensoring data for monitoring and control, and the dynamic reconfigurability of computations between the mobile unit and the stationary servers. Our effort in the area of ubiquitous computing involves the design and implementation of intelligent models and techniques to address the aforementioned obstacles. In this paper we present the architecture of an intelligent electronic notepad, called SciencePad, to support a scientist in the research environment of the future

On Learning and Adaptation in Multiagent Systems: A Scientific Computing Perspective

Systems with interacting agents are now being proposed to solve many problems grouped together under the "distributed problem solving" umbrella. For such systems to work properly, it is necessary that agents learn from their environment and adapt their behaviour accordingly. We investigate such systems in the context of scientific computing. The physical world consists of interacting system, and its overall behaviour emerges from the interacting local behaviours of its constituents.In this paper we present a system which uses a combination of neuro--fuzzy learning and static adaptation to coordinate the activity of multiple agents. An epistemic utility based formulation is used to automatically generate the exemplars for learning, making the process unsupervised. We illustrate how these techniques can be used to convert a standalone, single agent system into a collaborative, multiagent one, and present some results from a preliminary implementation. We also present the design..