Data Exploration or “What have those agents ever done for us?” Alasdair Allan University of Exeter, Exeter, U.K.

Slides:



Advertisements
Similar presentations
STAR Intelligent Agents and Web Services Alasdair Allan Tim Naylor University of Exeter Iain Steele Dave Carter Jason Etherton Chris Mottram Liverpool.
Advertisements

Robotic telescope networks, agent architectures and event messaging Alasdair Allan Tim Naylor Eric Saunders University of Exeter Iain Steele Chris Mottram.
Enrique Solano Márquez SVO Principal Investigator LAEX – CAB / INTA-CSIC The Spanish Virtual Observatory IVOA Interop., Garching, Nov 2009.
2 Introduction A central issue in supporting interoperability is achieving type compatibility. Type compatibility allows (a) entities developed by various.
CWE, EC – ESA joint activities on e-collaboration Brussels, 13 April 2005 IST Call 5 Preparatory workshop.
Large Scale Knowledge Management across Media Prof. Fabio Ciravegna, Department of Computer Science University of Sheffield
Abstraction Layers Why do we need them? –Protection against change Where in the hourglass do we put them? –Computer Scientist perspective Expose low-level.
MULTI-AGENT BASED SCHEDULING D. Ouelhadj ASAP (Automated Scheduling Optimisation and Planning) Research Group School of Computer Science and IT University.
Liverpool John Moores University & University of Exeter eScience Telescopes for Astronomical Research
The rise of the robots… Alasdair Allan School of Physics, University of Exeter Alasdair Allan School of Physics, University of Exeter.
A Heterogeneous Telescope Network Alasdair Allan Tim Naylor Eric Saunders University of Exeter Iain Steele Chris Mottram Liverpool John Moores University.
ESO-ESA Existing Activities Archives, Virtual Observatories and the Grid.
SFIDA-PMI Soluzioni informatiche per FIliere, Distretti ed Associazioni di PMI Genève – 24 Feb 2005 Matteo Villa TXT e-Solutions SpA.
Distributed Scheduling in Supply Chain Management Emrah Zarifoğlu
ASCR Data Science Centers Infrastructure Demonstration S. Canon, N. Desai, M. Ernst, K. Kleese-Van Dam, G. Shipman, B. Tierney.
EStar – Combining Telescopes and Databases Tim Naylor - University of Exeter Iain Steele – Liverpool John Moores University Dave Carter - Liverpool John.
The Business Value of CA Solutions Ovidiu VALEANU Senior Consultant DNA Software – CA Regional Representative.
Data Mining Techniques Cluster Analysis Induction Neural Networks OLAP Data Visualization.
1 Intelligent Agents Software analog to human agents real estate agent, librarian, salesperson Perform tasks individually, or in collaboration Static and.
0 General information Rate of acceptance 37% Papers from 15 Countries and 5 Geographical Areas –North America 5 –South America 2 –Europe 20 –Asia 2 –Australia.
Effective Coordination of Multiple Intelligent Agents for Command and Control The Robotics Institute Carnegie Mellon University PI: Katia Sycara
Distributed Network and System Management Based on Intelligent and Mobile Agents Jianguo Ding 25/03/2002 DVT-DatenVerarbeitungsTechnik FernUniversität.
8th Workshop "Software Engineering Education and Reverse Engineering", Durres RFAgent – an eLearning Supporting Tool Asya Stoyanova-Doycheva University.
Lecture 1: Introduction Slides adapted from Sobah Abbas Petersen
Semantic Web and Web Mining: Networking with Industry and Academia İsmail Hakkı Toroslu IST EVENT 2006.
Introduction and Overview “the grid” – a proposed distributed computing infrastructure for advanced science and engineering. Purpose: grid concept is motivated.
GenSpace: Exploring Social Networking Metaphors for Knowledge Sharing and Scientific Collaborative Work Chris Murphy, Swapneel Sheth, Gail Kaiser, Lauren.
The CrossGrid project Juha Alatalo Timo Koivusalo.
1 WEEK 10 Intelligent (Software) Agents. 2 Case Scenario Every year, ABC Enterprise will conduct annual general meeting (AGM) to report company performance.
Provisional draft 1 ICT Work Programme Challenge 2 Cognition, Interaction, Robotics NCP meeting 19 October 2006, Brussels Colette Maloney, PhD.
1 Chapter 7 IT Infrastructures Business-Driven Technology
RETSINA: A Distributed Multi-Agent Infrastructure for Information Gathering and Decision Support The Robotics Institute Carnegie Mellon University PI:
Intelligent Agents revisited.
Multiagent Systems: Local Decisions vs. Global Coherence Leen-Kiat Soh, Nobel Khandaker, Adam Eck Computer Science & Engineering University of Nebraska.
Autonomous observing The Astronomer’s Last Stand Alasdair Allan School of Physics, University of Exeter, UK Iain Steele Astrophysics Research Institute,
Software Architecture for Mobile Distributed Computing Presented by: Deepak N Lakshminarayanan The University of Texas at Dallas Under the Guidance of.
An Educational Project With An Astronomical Network Juan Ángel Vaquerizo Gallego on behalf of CESAR Team Centro de Astrobiología (CSIC-INTA) AstroRob 2013.
Agent architectures Smarter software for astronomers Alasdair Allan University of Exeter, Exeter, U.K.
Semantic Web & Service Platforms Technical Club Centre for Communication Systems Research Faculty of Engineering and Physical Sciences University of Surrey.
The rise of the robots… Alasdair Allan School of Physics, University of Exeter Alasdair Allan School of Physics, University of Exeter.
Requirements To Design--Iteratively Chapter 12 Applying UML and Patterns Craig Larman.
SmartGRID Ongoing research work in Univ. Fribourg and Univ. Applied Sciences of Western Switzerland (HES-SO) SwiNG Grid Day, Bern, Nov. 26th, 2009 Ye HUANG.
Implementing an Observational Grid Eric Saunders Alasdair Allan Tim Naylor University of Exeter Iain Steele Chris Mottram Liverpool John Moores University.
7-1 Management Information Systems for the Information Age Copyright 2004 The McGraw-Hill Companies, Inc. All rights reserved Chapter 7 IT Infrastructures.
Agent-oriented Knowledge Management in Learning Environments: A Peer-to-Peer Helpdesk Case Study Renata S. S. Guizzardi 1 Lora Aroyo 1 Gerd Wagner 2 1.
ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information.
Event Infrastructure Alasdair Allan University of Exeter Alasdair Allan University of Exeter Robert R. White Los Alamos National Laboratories The eSTAR/TALONS.
MOBILE AGENTS What is a software agent ? Definition of an Agent (End-User point of view): An agent is a program that assists people and acts on their behalf.
Responding to the Unexpected Yigal Arens Paul Rosenbloom Information Sciences Institute University of Southern California.
Access Control for Federation of Emulab-based Network Testbeds Ted Faber, John Wroclawski 28 July 2008
Rob Smith April 21, /18 GOLD Project Update Meeting GOLD an infrastructural approach to virtual organisations.
Grid Middleware Tutorial / Grid Technologies IntroSlide 1 /14 Grid Technologies Intro Ivan Degtyarenko ivan.degtyarenko dog csc dot fi CSC – The Finnish.
Grid-based Collaboration in Interactive Data Language Applications Minjun Wang Department of Electrical Engineering and Computer Science Syracuse University,
Advanced Technologies in Education Virtual Observatory 1 Virtual Observatory: D-Space Project Athens, 14 November 2004 Elena Tavlaki Head of Research Programs.
Bio-Networking: Biology Inspired Approach for Development of Adaptive Network Applications 21 May 2005Ognen Paunovski Bio-Networking: Biology Inspired.
GRID Overview Internet2 Member Meeting Spring 2003 Sandra Redman Information Technology and Systems Center and Information Technology Research Center National.
Enabling e-Research in Combustion Research Community T.V Pham 1, P.M. Dew 1, L.M.S. Lau 1 and M.J. Pilling 2 1 School of Computing 2 School of Chemistry.
By, Naga Manojna Chintapalli. CHAPTER 2.2 TRANSPARENCY.
Introspecting Agent-Oriented Design Patterns Manuel Kolp, T. Tung Do, Stéphane Faulkner and T. T. Hang Hoang Presented by Rachel Bock, Sam Shaw, Nicholas.
JSPG Update David Kelsey MWSG, Zurich 31 Mar 2009.
Smart Web Search Agents Data Search Engines >> Information Search Agents - Traditional searching on the Web is done using one of the following three: -
Building a worldwide interoperable data infrastructure for astronomy: the International Virtual Observatory Alliance SciDataCon 2016, Denver, 13/Sept/2016.
Organization and Knowledge Management
IPv6 within the Australian Government
Enterprise Systems Architectures
Agents & Agency What do we mean by agents? Are agents just a metaphor?
Introduction to TIMAN: Text Information Managemetn & Analysis
Gail Kaiser, Swapneel Sheth, Chris Murphy
In Distributed Systems
Presentation transcript:

Data Exploration or “What have those agents ever done for us?” Alasdair Allan University of Exeter, Exeter, U.K.

24th Feb. 2005VOTech Planning Meeting 1 Agent architectures? An agent is “just software” not magic Most successful agent architectures are based on partial plan approaches Most multi-agent systems are based on the collaborative agents paradigm

24th Feb. 2005VOTech Planning Meeting 2 Multi-agent systems A multi-agent system is one that consists of a number of agents, which interact with one-another In the most general case, agents will be acting on behalf of users with different goals and motivations To successfully interact, they will require the ability to cooperate, coordinate, and negotiate with each other, much the same as “real” people

24th Feb. 2005VOTech Planning Meeting 3 Multi-agent systems are about … Decision making Asking questions Brokering agreements –Carrying out resource discovery could mean that your agent looks to your collaborators agent for data and expertise before it looks to “central” sources.

24th Feb. 2005VOTech Planning Meeting 4 Data mining Collaborative agents operate in a flat world, they can access proprietary data from a collaborator just as easily as public data from a “central” source Agents can encapsulate knowledge, and retrieve data that will be “good enough” to get the job done…

24th Feb. 2005VOTech Planning Meeting 5 Data mining Encapsulating knowledge in the VO means that we can generate high level science products High level products can be used as the basis for decision making Every decision made means that the learning curve for the user is that much shallower

24th Feb. 2005VOTech Planning Meeting 6 Data exploration Astronomers will want to combine their own data with data from the VO Proprietary data, both their own, and data belonging to collaborators New data and event notification in real time directly from the observatories

24th Feb. 2005VOTech Planning Meeting 7 What they have done for us … Agent architectures proved to be a big win for robotic telescopes networks Using agent architectures increased our flexibility, scalability and autonomy Real time systems needed robustness, agent architectures provided it

24th Feb. 2005VOTech Planning Meeting 8 Suggestions? I think we should investigate science and infrastructure use cases for agents Build prototypes for resource discovery and data exploration to see if they can provide a similar win for the VO