NRL Coalition Agents Experimentation Participation

Slides:



Advertisements
Similar presentations
Semantic Web for the Military User C4 Summary of Actions From June 6/7 Meeting.
Advertisements

CoABS Grid Military Users Group (GMUG) for the SWMU Tom Martin November 13, 2001 for LCDR Dylan Schmorrow CoABS Program Manager
Semantic Web for the Military User C2 Applications Breakout Report 11/14/01.
1 Artificial Intelligence Applications Institute, University of Edinburgh, UK Institute for Human and Machine Cognition, Pensacola, Florida AI Planning.
1 Artificial Intelligence Applications Institute, University of Edinburgh Institute for Human & Machine Cognition, University of West Florida CoSAR-TS.
1 Artificial Intelligence Applications Institute, University of Edinburgh Institute for Human & Machine Cognition, University of West Florida CoSAR-TS.
Fundamental Theme for ESG Support to Operational and Tactical Forces Time PARTICIPATIONPARTICIPATION.
2 Artificial Intelligence Applications Institute, University of Edinburgh, UK Institute for Human and Machine Cognition, Pensacola, Florida CoSAR-TS Coalition.
Klas Wallenius Common and Individual Situation Awareness from a Technical Point of View Klas Wallenius.
CoAX – Coalition Agents eXperiment AIAI, BBN, CMU, U.Dartmouth, DSTO, GITI, Lockheed Martin ATL, U.Maryland, U.Michigan, Potomac Inst., QinetiQ, USC/ISI,
Tactical Event Resolution Using Software Agents, Crisp Rules, and a Genetic Algorithm John M. D. Hill, Michael S. Miller, John Yen, and Udo W. Pooch Department.
Force XXI Battle Command Brigade and Below (FBCB2) Communications System
Naval Research Laboratory (NRL) Technology Integration Experiments (TIE) Status Briefing at CoAX Meeting April 2002 Toulouse, France Ranjeev Mittu US Naval.
CNRIS CNRIS 2.0 Challenges for a new generation of Research Information Systems.
1 CISR-consultancy Challenges “Customer ask us what to do next” Keywords: “Customer ask us what to do next” From Policy to Practise The world is going.
© 2002 Intelligent Software Agents Lab, CMU Katia O O O R O R R O O R Joe X R X X R X X R R X RETSINA Group O: Files created and owned by Katia. Joe cannot.
An Ad Hoc Network Taxi Dispatch System E Huang Digital Technology Group Computer Laboratory University of Cambridge.
1 CACTUS: Context Aware Communications, Terminal, and User.
1 “Building on CoAX 2001 Success”; Patrick Beautement, QinetiQ Patrick Beautement, QinetiQ, Jeffrey M. Bradshaw,
DARPA CoABS Grid (GITI, ISX) Coalition Agents eXperiment - CoAX DARPA CoABS, AFRL, BBN, Boeing, DSTL, DREV, DSTO, Dartmouth, Edinburgh/AIAI, LM-ATL, OBJS,
Operational Capability: We are developing and testing search munition control strategies using both a high fidelity 6-dof simulation of the LOCAAS and.
Wireless Sensor Network for Tracking the Traffic in INTERNET Network Routers Supervisor: Mark Shifrin Students: Yuriy Kipnis Nir Bar-Or Networked Software.
Robots at Work Dr Gerard McKee Active Robotics Laboratory School of Systems Engineering The University of Reading, UK
“Mobile Class”: A Cloud-Based mobile learning system: Shanghai lifelong learning network’s “Mobile Cloud learning" prototype Dr. Minjuan Wang Designer.
Distributed Real-Time Systems for the Intelligent Power Grid Prof. Vincenzo Liberatore.
Multiple Autonomous Ground/Air Robot Coordination Exploration of AI techniques for implementing incremental learning. Development of a robot controller.
HPC use in Testing Ad Hoc Wireless Sensor Networks
Networks for Security Applications Defense Security Innovation Quebec City, Nov. 16, 2007 Prof. Howard M. Schwartz.
1 World Wide Consortium for the Grid Global Grid Forum Network-Centric Operations Community Session 28 June
Intelligent Large Scale Sensing Systems (ILS 3 ) initiative Initiative Status and Activities Kevin M. McNeill, PhD Research Assoc. Professor Director,
NSF Industry-University Cooperative Research Center for Advanced Knowledge Enablement NOA Inc DBA TerraFly Inc IBM Naphtali Rishe Control and mapping of.
Introduction Infrastructure for pervasive computing has many challenges: 1)pervasive computing is a large aspect which includes hardware side (mobile phones,portable.
5 PR Praktikum aus Informatik Gabriele Kotsis Summer Term 2009.
Network UAV C3 Stage 1 Final Briefing Timothy X Brown University of Colorado at Boulder Interdisciplinary Telecommunications Program Electrical and Computer.
Coalition Agents eXperiment (CoAX) The Coalition TIE AFRL Rome, AIAI, Boeing, Dartmouth, DERA Malvern, Lockheed.
Competitive Advantages SyAM Software believes our core competitive strengths include: –Ease of use and installation –Our software’s dynamic discovery,
CoAX – Coalition Agents eXperiment AIAI, BBN, CMU, Dartmouth, DSTO, GITI, Lockheed Martin ATL, NRL, Potomac Inst., U.Maryland, U.Michigan, QinetiQ, UT-Austin,
Distribution A: Approved for public release; distribution is unlimited Get the right M&S technology to the right place, at the right time, for the Decision.
A Robotic Middleware Jagiello, J., Tay, N., Eronen, M. Defence Science and Technology Organisation, Canberra, Australia
WASP Airborne Data Processor Laboratory for Imaging Algorithms and Systems Chester F. Carlson Center for Imaging Science Rochester Institute of Technology.
University of Pennsylvania 1 GRASP Cooperative Control and Coordination of Multiple Robots Vijay Kumar GRASP Laboratory University of Pennsylvania
1 Artificial Intelligence Applications Institute Centre for Intelligent Systems and their Applications A Shared Model for Mixed-initiative Synthesis Tasks.
By Miguel A. Erazo Advisor: Jason Liu March 2009.
Project number: ENVRI and the Grid Wouter Los 20/02/20161.
New ELICIT Software Platform Capabilities and Campaign 13 th ICCRTS, I-079, June 2008 Mary Ruddy Mark Nissen
1 WANTED A FEW GOOD AGENTS 2 Knowledge Systems for Coalition Operations 24 April 2002 Enabling Real-time Operations in Coalitions. LCDR Dylan Schmorrow,
MIT Lincoln Laboratory Dynamic Declarative Networking Exploiting Declarative Knowledge To Enable Energy Efficient Collaborative Sensing Daniel J. Van Hook.
Mobile Analyzer A Distributed Computing Platform Juho Karppinen Helsinki Institute of Physics Technology Program May 23th, 2002 Mobile.
Dr. Stelios Panagiotou, Dr. Stelios C.A. Thomopoulos Integrated Systems Laboratory Institute of Informatics and Telecommunications National Center for.
© 2016 TM Forum Live! 2016 | 1 E2E Service Orchestration for Smarter Health Real-World Business User Stories Draft.
1 U.S. Naval Forces Europe U.S. Naval Forces Africa Commander SIXTH FLEET “Maritime Domain Awareness Perspectives” Mediterranean Security 2012 January.
Air Force Institute of Technology
IoT Business Maturity Model 1. Operational efficiency
MOBILE AD-HOC NETWORKS
Joint Command and Control
MetaOS Concept MetaOS developed by Ambient Computing to coordinate the function of smart, networked devices Smart networked devices include processing.
Constructs agent’s situational picture from messages and sensor input
CoAX - Coalition Agents Experiment
Dipanjan Chakraborty Anupam Joshi CSEE University of Maryland Baltimore County Anamika: Distributed Service Discovery and Composition Architecture for.
Field Teams and Wireless Networks
Deep learning Concept Objectives Accomplishments and Impact
Large-Scale Mobile-Agent Systems
DARPA Coalition Agents eXperiment - CoAX DARPA CoABS, AFRL, BBN, Boeing, DSTL, DSTO, Dartmouth, UEdinburgh/AIAI, LM-ATL, OBJS, QinetiQ, UMichigan, USC/ISI,
A survey on Bio inspired Routing in MANETs
Business Document Platform
Institute for Human and Machine Cognition, UWF, Pensacola, FL
Enhanced State Estimation by Advanced Substation Monitoring
Harness Network Data and Artificial Intelligence
Molly Donohue Magee, Executive Director June 2019
Presentation transcript:

NRL Coalition Agents Experimentation Participation Ranjeev Mittu, mittu@ait.nrl.navy.mil Naval Research Laboratory Description: Part of CoAX – Coalition Agents Experiment. Demonstrate Command and Control system’s ability to integrate coalition data from the CoABS grid in support of The Technical Cooperation Program’s (TTCP) Binni scenario. Supporting the Maritime domain in the demonstration Results: Integration of Command and Control system “surrogate” via the CoABS grid with agents from: BBN (Simworld agent) Univ. of MD (Track Prediction agents) Univ. of Texas (Fusion Agent) Univ. of W. Fl. (KaOS Domain Registration) QinetiQ (Alert Agents) Future: Building upon CoAX and CoABS research in support of DMSO: Intelligently monitoring simulations from GCCS. NRL MASAM: Software agents to process data/information and provide to airborne platforms in operating in high-connectivity battlefield. Mobile Ad-Hoc Networking (MANET): Application of mixed-initiative and teamwork models. Consistent Network Information Stream: MAS for enhancing the COP