8. Atkinson - AOARD Information Sciences

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David J. Atkinson, Ph.DProgram Manager

AFOSR/AOARDAir Force Research Laboratory

AFOSR

AOARD: INFORMATION SCIENCES

AFOSR: ROBUST COMPUTATIONALINTELLIGENCE

14 March 2011

Distribution A: Approved for public release; distribution is unlimited. 88ABW-2011-0772


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2011 AFOSR SPRING REVIEWAOARD INFORMATION SCIENCES

NAME: David J. Atkinson, Ph.D (Program Manager)TEAM: Prof. Hiroshi Motoda (Senior Scientific Advisor)Peter Friedland, Ph.D (Senior Scientific Advisor)

DESCRIPTION OF PORTFOLIO:

Information Sciencesin Asia. Covers theoretical and experimental workin computer science and intelligent systems aligned with needs ofAFOSR/RSL programs, AFRL technical directorate challenges, andemerging topics of special significance

SUB-AREAS: Intelligent systems(machine-learning, human-computer interaction,computer sensing and perception, sensor networks, automated reasoning)

Trusted Systems(cyber-security, formal software verification)


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2011 AFOSR SPRING REVIEWAFOSR ROBUST COMPUTATIONAL INTELLIGENCE

NAME: David J. Atkinson, Ph.D (Program Manager)TEAM: Peter Friedland, Ph.D (Senior Scientific Advisor)

DESCRIPTION OF PORTFOLIO:

Theoretical and experimental work in artificial intelligence and related

disciplines focused on creating robust intelligent autonomous systemsthat are able to operate effectively: in novel situations despite gaps,conflicts and ambiguities in knowledge; that learn, adapt and improve withexperience; and that function at a level of flexibility and generalitycomparable to that of humans and animals

SUB-AREAS:

Knowledge representation, cognitive architectures, automated reasoning,machine learning and adaptation, meta-cognition, human-machineinteraction


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Challenging and Exciting ScienceAOARD Information Sciences

Machine understanding of implicit human intention

Who: K. Kosuge (JAPAN), S.Y. Lee (KOREA), F. Chen (AUSTRALIA)

Impact: Enable highly adaptive, intuitive and responsive human-computer, human-robot interaction in high cognitive workload tasks

Formal verification of very large and complex software codes

Who: G. Klein, G. Heiser (AUSTRALIA) Impacts:

Automated verification and eventually self-verifying codes

Enable enormous reduction in software lifecycle costs and reduced operationalrisk from residual software defects

Enable large-scale provably-correct integration of formal logic systems fortrustworthy autonomous systems

Harden VPN traffic against statistical fingerprinting techniques

Who: K. Anagnostakis (SINGAPORE)

Impact: Enable adaptive traffic concealment methods to prevent attacks


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Transformational CapabilityAFOSR Robust Computational Intelligence

Autonomous SystemsThe ability of a system, without human intervention, to compose and selectamong different courses of action to accomplish goals based on its knowledgeand understanding of the world and the exigencies of the moment.

IMPACTS

Potential enormous

increases in capabilities

Significant time-domainoperational advantages, i.e.,

operational tempo

Manpower efficiencies and

cost reductions

--Technology Horizons 2010 Report

CAPABILITIES

Robust and Trustworthy - the system will functioncorrectly, i.e., as designed and as we intend, despite

a real world that is messy, ambiguous, dynamicandadversarialincluding the risk of system faults

Cognitive software system architectures bring

together multiple specialized AI components

Problem-solving using integrated heterogeneousreasoning techniques

Flexible autonomy via human-machine interaction;machines as partners, not simply tools


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Non-Robust / Robust

Doesnt learn from experience

Hard failure

Constantly learning and adapting

Stays on mission despite near-crippling system failures


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RCI Program Engagement withOther Research Organizations

Our Niche: Emphasis on systems approach to achieving significant

improvements in robustness of intelligent systems

National Science Foundation

Briefed to CISE/IIS PMs during formulation with continuing discussions

US multi-agency information exchange in AI, Robotics

Facilitating international cooperative research for NSF with Japan and Korea

Office of Naval Research

Briefed to C4ISR PMs during formulation with continuing discussions

Supporting formulation of new ONR program in Machine Reasoning

DASA, Army Research Laboratory / TARDEC Shared direction of research grants, provided programmatic and technical support

to international robotics challenge jointly sponsored with DSTO (Australia)

Briefed ARL Chief Scientist for Robotics, branch chief and other personnel duringformulation of RCI; continuing discussions.


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Recent TransitionsAOARD Information Sciences

Formal System Verification for Trustworthy Embedded Systems

Researching methods for formally integrating heterogeneous logic systems inapplication area of model-based software verification

PI: Dr. Gerwin Klein, National ICT Australia (NICTA), Sydney, AU

Partner: Steven Drager, AFRL/RITB, co-funding, host PI visit, guiding future directions

Neuroergonomic Research for Online Assessment of Cognitive Workload

Research on the integration and selection of robust cognitive workload measuressuch as speech signals and EEG

PI: Dr. Fang Chen, National ICT Australia (NICTA), Sydney, AU

Partner: Dr. James Christensen, AFRL/RHCP, co-funding, hosted PI visit, developingCooperative Research Agreement to aid integration of research studies, methods, tools, data

Multi-Agent Sensor Network Systems Characterizing UAV sensor network robustness to loss of nodes and links

PI: Prof. Brian Anderson, Australia National University, Canberra, AU

Industry: Facilitated introduction to Boeing R&TD Center (Seattle) which now has separatecontract with Prof. Anderson to mature research on UAV sensor formation control


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Recent Transitions (2)AOARD Information Sciences

Sensor Data Integrity and Mitigation of Perceptual Failures Researching methods for automatic detection and mitigation of faults and uncertainty in sensor

data and machine perception

PI: Dr. Thierry Peynot, ARC Center for Autonomous Systems, University of Sydney, Sydney, AU

Partner: Brian Skibba, AFRL/RX, strong advocacy, research data to be used to help refinerobotic sensor requirements

Multi-Autonomous Ground-robotic International Challenge (MAGIC 2010)

Jointly sponsored by DARPA, ARL, ONRG, AOARD and Australia DSTO

Research, develop and demonstrate a multi-vehicle robotic team to survey, map,

recognize and respond to threats in a dynamic urban environment AOARD issued and jointly directed multiple research grants to 10 teams and

contributed technical expertise to the governing technical team.

AFRL/RX (B. Skibba) participated on leadership team and as a judge

The challenge demonstration was held in Adelaide, November 2010.

AOARD jointly directing follow-on grants to the top three research teams.


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Research Examples

AOARD Information Sciences Measuring and Ensuring Performance and Information Quality in Multi-Agent

Sensor Network Systems

Prof. Brian Anderson, Australia National University and National ICT Australia

AFOSR Robust Computational Intelligence

Extending Semantic and Episodic Memory to Support Robust Decision Making

Prof. John Laird, University of Michigan


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Measuring and Ensuring Performance and InformationQuality in Multi-Agent Sensor Network Systems

PI: Prof. Brian Anderson, Australian National University and NICTA, Canberra, AU

Scientific Objective:

Characterize a sensor networks ability to continue performing given a lossof psensing agents and/or qcommunication links

Key performance aspect is localizability: Localizability is the ability to determine the position of all nodes given certain internode

distances and the absolute position of a limited number of anchor nodes)

Scientific/Technical Approach:

Build on a graph theory characterization of sensor network localizabilityusing graph rigidity analysis

Breakthrough Opportunity:

Network tolerance to enemy attacks and jamming.

Network tolerance to loss of multiple sensors and links due to powerdegradation etc.

Results are applicable to other network properties (e.g., formation control)


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Insight: Localizability Based OnA Test for Graph Rigidity

Two types of nodes: anchors and (ordinary) sensors.

Anchor positions known; certain internodedistances are measured - typically betweenclose nodes (unit disk model).

Localization is the task of finding theposition of all nodes given the measurements.

The characterization of localizable networks is given in terms of graphtheoretical properties of the network topology. A network is localizable if itis globally rigidand there are three non collinear anchor nodesin the network.

Rigid network = intuitive notion: if one builtthe network with bars and joints then theresulting framework would not flex

Redundant Rigidity = remains rigid afterremoval of any edge

Global Rigidity = redundant rigidity + 3-connectedness

MINIMALLY RIGID NONRIGID

NONRIGIDRIGID, BUT NOT

MINIMALLY SO; this isredundant rigidity

a b a b

cda

d cc

ba

d

cd


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Anderson - Progress

A set of combinatorial conditions was found for robustness to node loss.

This is the first timeanyone has considered localization robustness to multiplenode/link losses (the general case).

Showed that it is sufficientfor a network to have certain connectivity conditionsinorder to be robust against node loss.

There is a small threshold for the transmission range of nodesbeyond which the

network will obtain the desired robustness against the loss of nodes.

Several minimal link count structures which are robustly localizable tothe loss of up to 2 nodes are proposed for the first time (general claim fornnodes is future research).

Surprising Discovery: The energy required for having adesignated large percentage of nodes (e.g. 99%) connectedis asymptotically and vanishingly smallcomparedwith that required for having a 100% connected network!=> In a large scale network the overallperformance may improve significantly by leaving fewhard-to-reach nodes out of robustness requirements.

S


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Extending Semantic and Episodic Memory toSupport Robust Decision Making

PI: Prof. John Laird, University of Michigan

Scientific Objective:

Develop a general, robust cognitive architecture that can be used as thebasis for creating artificial agents

Effectively use large databases of knowledge for reasoning

Learning diverse knowledge from experience

Scientific/Technical Approach: Within the context of the existing Soar architecture

New algorithms for semantic and episodic memory functionality, while alsomeeting real-time performance requirements

Investigate functional and algorithmic synergies of semantic and episodic

memory in support of problem-solving reasoning

Breakthrough opportunity:

Artificial agents that perform integrated diverse forms of reasoning with largesources of experiential knowledgeand massive existing databases


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Soar Cognitive ArchitectureBackground

Soar embodies a theory of cognitive computationbased on goals, problem spaces, states andoperators (one of several theories and architectures; another is ACT-R)

Uses a wide variety of knowledge representations(procedural, declarative, episodic)

Data-driven decision-elaboration-action cycletransforms existing state into the goal state

Implements a wide variety of reasoning techniques

Uses heuristicsand other methods to proceed in ambiguous situations

Long TermMemories

Active Memory& Reasoning

Perception &Action

Learning &Remembering


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Laird - Progress

Real-Time Performance

Characterized new alternative algorithms forworking memory, semantic memory andepisodic memory in robot test apparatus at


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Portfolio Topic OverviewAOARD Information Sciences

Autonomous systems Machine-learning

Human-computer interaction

Computer sensing and perception Automated reasoning

Autonomous mobile sensor networks

Trusted systems Cyber-security

Formal software verification

P tf li T i O i


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Portfolio Topic OverviewAFOSR Robust Computational Intelligence

Knowledge representation Cognitive architectures

Automated reasoning

Machine learning Meta-cognition

Human-machine interaction

Cognitive robotics


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Wrap-up

Thank you very much for your attention!

Contact Info (as of 1 April 2011)

David J. AtkinsonInstitute for Human and Machine [email protected]


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Backup

Projects, PIs and Institutions Conferences and Workshops

Recent Publications


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Projects

Understanding how to build long-lived learning collaboratorsPI: Prof. Kenneth Forbus, Northwestern University, Contact: [email protected]

"Intelligence in the Now: Robust Intelligence in Complex DomainsPI: Prof. Leslie Kaebling, MIT; Co-I: Prof. Tomas Lozano-Perez, MIT Contact: [email protected]

Extending Semantic and Episodic Memory to Support Robust Decision Making

PI: Prof. John Laird, University of Michigan, Contact: [email protected]

"A Unified Architectural Approach to the Hybrid Mixed Challenge of Situational Assessment and Prediction

Prof. Paul Rosenbloom, University of Southern California, Contact: [email protected]

"Contextual Awareness for Robust Robot Autonomy

Dr. Reid Simmons, Carnegie Mellon University, Contact: [email protected]

"Robust Multi-Agent Sensor Network Systems

Prof. Brian D. O. Anderson, NICTA-Canberra and Australia National University, Contact: [email protected]

Integrating Logical and non-Logical ReasoningPI: Prof Maurice Pagnucco, University of New South Wales, Contact: [email protected]

"Sensor Data Integrity and Mitigation of Perceptual Failures

Dr. Thierry Peynot, University of Sydney; Co-I: Dr. Hugh Durrant-Whyte, NICTA (CEO), Contact: [email protected]

Learning Within Optimization

PI: Prof Toby Walsh, NICTA Sydney, Contact: [email protected]

"Human-Robot Interaction: Intention Recognition and Mutual EntrainmentProf. Kazuhiro Kosuge, Tohoku University, Contact: [email protected]

Machine Understanding of Implicit Human Intention

PI: Prof. Soo-Young Lee, Korea Advanced Institute of Science & Technology (KAIST), Contact: [email protected]

Formal System Verification for Trustworthy Embedded Systems Continuation

PI: Dr. Gerwin Klein, Co:I: Dr. Gernot Heiser, NICTA-Sydney, Contact: [email protected]

Hardening Encrypted VPNs against Statistical Fingerprinting Attacks

PI: Dr. Kostas Anagnostakis, Niometrics Pte Ltd, Contact: [email protected]

Automatic Multimodal Cognitive Load Measurement

PI: Dr. Fang Chen, NICTA Sydney, Contact: [email protected]
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


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Projects (Cont.)

Discovering hidden causal structure in data

PI: Prof. Takashi Washio, Osaka University, Contact: [email protected]

A density ratio approach to machine learningPI: Prof. Masashi Sugiyama, Tokyo Institute of Technology, Contact: [email protected]

Mass estimation and its applications

PI: Dr. Kai Ming Ting, Monash University, Contact: [email protected]

Security Protocol Verification and Optimization by Epistemic Model Checking

PI: Prof. Ronald van der Meyden, University of New South Wales, Contact: [email protected]

Transfer Learning for Adaptive Relation Extraction

PI: Dr. Hai-Leong Chieu, DSO National Laboratories, Contact: [email protected]

MAGIC 2010 The Virginia Tech Team

PI: Prof. Tomonari Furukawa, Virginia Polytechnic Institute and State University, Contact: [email protected]

MAGIC 2010 The Univ. Pennsylvania and BAE Systems TeamPI: Dr. Daniel D. Lee, University of Pennsylvania, Contact: [email protected]

MAGIC 2010 Competition - University of MichiganPI: Prof. Edwin Olson, University of Michigan, [email protected]

MAGIC 2010 - The Cornell TeamPI: Prof. Mark Campbell, Cornell University, Contact: [email protected]

MAGIC 2010 The Robotic Research TeamPI: Alberto Lacaze, Robotic Research LLC, Contact: [email protected]

MAGIC 2010 - The Strategic Engineering TeamPI: Richard Alpin, Strategic Engineering Pty Ltd., Contact: [email protected]

MAGIC 2010 - The Kingston TeamPI: Maj. Marc Fricker, The Royal Military College of Canada, Contact: [email protected]

MAGIC 2010 Competition - Flinders UniversityPI: Prof. David Powers, Flinders University, Contact: [email protected]

MAGIC 2010 The Chiba TeamPI: Mark Haley, Analytical Software Inc. Co-I: Prof. Kenzo Nonami, Chiba University, Contact: [email protected]

MAGIC 2010 The ASELSAN TeamPI: Faruk Menguc, ASELSAN A.S. Defence Systems , Contact: [email protected]
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


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Conferences and Workshops

Annual Conference of the Prognostics and Health Management Society 2010, Portland, ORhttp://www.phmconference.org/

The Ninth International Workshop on the Algorithmic Foundations of Robotics (WAFR), Singapore,http://www.wafr.org/

The First International Conference on Future Generation Information Technology, Jeju, Korea,http://www.sersc.org/FGIT2009/

The 22nd Australasian Joint Conference on Artificial Intelligence, Melbourne, Australia,http://www.infotech.monash.edu.au/about/news/conferences/ai09/

9th ACM SIGGRAPH Intl Conf. on VR Continuum and Its Applications in Industry, Seoul, Korea,

http://www.vrcai2010.org/VSMM2010 (16th Intl Conf. on Virtual Systems and Multimedia), Seoul Korea, http://www.vsmm2010.or.kr/

PAKDD 2010: The 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Hyderabad, India,http://www.iiit.ac.in/conferences/pakdd2010/

PRICAI 2010: The 11th Pacific Rim International Conference on Artificial Intelligence, Daegu, Korea,http://www.pricai2010.org

The 10th IEEE International Conference on Data Mining (ICDM 2010), Sydney, Australia,

http://datamining.it.uts.edu.au/icdm10/

The 13th International Conference on Discovery Science, Canberra, Australia,http://www.cse.unsw.edu.au/~achim/DS10/

2010 IEEE-RIVF International Conference on Computing and Telecommunication Technologies (IEEE-RIVF 10),Hanoi, Vietnam, http://www.rivf.org

The Fifth International Conference on Knowledge, Information and Creativity Support Systems (KICSS 2010),Chiang Mai, Thailand, http://itpe.siit.tu.ac.th/kicss2010/ http://www.kicss2010.org

The Second Asian Conference on Machine Learning, Tokyo, Japan, http://sugiyama-www.cs.titech.ac.jp/ACML2010/
http://www.phmconference.org/http://www.wafr.org/http://www.sersc.org/FGIT2009/http://www.infotech.monash.edu.au/about/news/conferences/ai09/http://www.vrcai2010.org/http://www.vsmm2010.or.kr/http://www.iiit.ac.in/conferences/pakdd2010/http://www.pricai2010.org/http://datamining.it.uts.edu.au/icdm10/http://www.cse.unsw.edu.au/~achim/DS10/http://www.rivf.org/http://itpe.siit.tu.ac.th/kicss2010/http://www.kicss2010.org/http://sugiyama-www.cs.titech.ac.jp/ACML2010/http://sugiyama-www.cs.titech.ac.jp/ACML2010/http://sugiyama-www.cs.titech.ac.jp/ACML2010/http://sugiyama-www.cs.titech.ac.jp/ACML2010/http://www.kicss2010.org/http://itpe.siit.tu.ac.th/kicss2010/http://www.rivf.org/http://www.cse.unsw.edu.au/~achim/DS10/http://datamining.it.uts.edu.au/icdm10/http://www.pricai2010.org/http://www.iiit.ac.in/conferences/pakdd2010/http://www.vsmm2010.or.kr/http://www.vrcai2010.org/http://www.infotech.monash.edu.au/about/news/conferences/ai09/http://www.sersc.org/FGIT2009/http://www.wafr.org/http://www.phmconference.org/


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Recent Publications

Agangostakis, K. G. Portokalidis, P. Homburg, and H. Bos, Paranoid Android: Versatile Protection For Smartphones ACSAC10,http://www.cs.columbia.edu/~porto/Publications_files/paranoidandroid_acsac10.pdf

Al-Bataineh, O. and R. van der Meyden Epistemic Model Checking for Knowledge-Based Program Implementation: an Application toAnonymous Broadcast,, SecureComm'10, 6th International ICST Conference on Security and Privacy in Communication Networks,Singapore, Sept 7-9 2010.

Al-Bataineh, Omar I., Ron van der Meyden: Abstraction for Epistemic Model Checking of Dining Cryptographers-based Protocols CoRRabs/1010.2287: (2010), submitted for publication

Andronick ,J., From a proven correct microkernel to trustworthy large systems, Proc. 1st International Conference on Formal Verification ofObject-Oriented Software (FoVeOOS10), volume 6528 of LNCS, Springer-Verlag, Paris, France, June, 2010 Invited talk

Andronick J., and D. Greenaway and K. Elphinstone, Towards proving security in the presence of large untrusted components , Proc. 5thWorkshop on Systems Software Verification, Vancouver, Canada, October, 2010

Berthold, Timo, Thibaut Feydy and Peter J. Stuckey. Rapid Learning for Binary Programs, Integration of AI and OR Techniques in ConstraintProgramming for Combinatorial Optimization Problems, 7th International Conference, CPAIOR 2010, Bologna, Italy, June 14-18, 2010.

Bessiere Christian, and George Katsirelos, Nina Narodytska, Claude-Guy Quimper, Toby Walsh. Propagating Conjunctions of All DifferentConstraints. Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2010, Atlanta,Georgia, USA, July 11-15, 2010.

Chen, S., Epps, J. and Chen, F., Eye Activity as a Measure of Human Mental Effort in HCI, Proc. International Conference on Intelligent

User Interfaces (IUI11), Palo, Alto, U.S.A., February 2011, to appear.

Derbinsky, N., Laird, J. E., Smith, B. Efficient fact retrieval from large semantic memories, Towards Efficiently Supporting Large Symbolic

Declarative Memories, ICCM 2010

Derbinsky, N., Laird, J. E., Efficient incorporation of environmental regularities to bias semantic retrievals, A Preliminary Functional Analysisof Memory in the Word Sense Disambiguation Task, AISB 2011 (submitted)

Heiser, G., and J. Andronick, K. Elphinstone, G. Klein, I. Kuz and L. Ryzhyk, The road to trustworthy systems, Proc. 5th Workshop onScalable Trusted Computing, Chicago, IL, USA, October, 2010 Invited paper

Huang, B., Yu, C., Anderson, B.D.O. and Mao, G., Connectivity-based Distance Estimation in Wireless Sensor Networks, IEEE Globecom
http://www.cs.columbia.edu/~porto/Publications_files/paranoidandroid_acsac10.pdfhttp://www.cs.columbia.edu/~porto/Publications_files/paranoidandroid_acsac10.pdf


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Recent Publications (2)

Huang, B., Yu, C., Anderson, B.D.O., Analyzing error propagation in 1-D sensor network localization, IEEE Trans Aerospace and ElectronicSystems

Huang, B., Yu, C and Anderson, B.D.O., Estimating distances by connectivity in wireless sensor networks, Computer Networks

Kaelbling, Leslie Pack And Tomas Lozano-Perez. Hierarchical Task And Motion Planning In The Now, Accepted For IEEE InternationalConference On Robotics And Automaton, May 2011.

Klein, G., The L4.verified Projects - Next Steps ,Proc. 3rd International Conference on Verified Software: Theories, Tools, Experiments(VSTTE'10), volume 6217 of LNCS, pages 86-96, Springer 2010 -- Extended abstract, invited talk

Klein, G., From a Verified Kernel towards Verified Systems, Proc. 8th Asian Symposium on Programming Languages and Systems(APLAS'10), volume 62461 of LNCS, pages 21-33, Springer 2010. -- Extended abstract, invited talk

Klein, G., A Formally Verified OS Kernel. Now What?,Proc. 1st Intl. Conf. Interactive Theorem Proving (ITP'10), volume 6172 of LNCS,

pages 1-7, Springer 2010 -- Extended abstract, invited talk

Klein, G., and J. Andronick, K. Elphinstone, G. Heiser, D. Cock, P. Derrin, D. Elkaduwe, K. Engelhardt, R. Kolanski, M. Norrish, T. Sewell, H.Tuch and S. Winwood,, seL4: Formal verification of an OS kernel, Communications of the ACM, 53(6), 107115, (June, 2010)

Khawaja, M. A., Chen, F. and Marcus, N., Using Language Complexity to Measure Cognitive Load for Adaptive Interaction Design, Proc.

International Conference on Intelligent User Interfaces (IUI10), Hong Kong, China, February 2010, pp. 333-336.

Kuz, I., and G. Klein, C. Lewis and A. Walker, capDL: A language for describing capability-based systems, Proc. 1st Asia-Pacific Workshopon Systems, New Delhi, India, August, 2010

Laird, J. E., Derbinsky, N., Voigt, J. Large-scale performance evaluation of declarative memories in mobile robot domain, Performance

Evaluation of Declarative Memory Systems in Soar, BRIMS 2011 (submitted)

Le, P., Epps, J., Ambikairajah, E. and Sethu, V., Robust Speech-Based Cognitive Load Classification Using a Multi-band Approach, Proc.APSIPA Annual Summit and Conference (APSIPA 10), Biopolis, Singapore, December 2010, to appear.

Le, P., Epps, J., Choi, E. and Ambikairajah, E., A Study of Voice Source and Vocal ract Filter Based Features in Cognitive Load

Classification, Proc. International Conference on Pattern Recognition (ICPR10), Istanbul, Turkey, August 2010, pp. 4516-4519.

Liu, J., Morse, A.S., Anderson, B.D.O., Yu, C., and Mou, S., Deterministic gossiping with a request-based protocol, IFAC World Congress2011, Milano.


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Mao, G. and Anderson, B.D.O., On the asymptotic connectivity of random networks under the random connection model , IEEEInfocom 2011

Mao, G., Zhang, Z. and Anderson, B.D.O., Probability of k-hop connection under random connection model, IEEE Communications LettersMao, G. and Anderson, B.D.O., On the asymptotic distribution of the number of isolated nodes under the random connection model, IEEE

Transactions Information Theory

Melchior, N. A. and R. Simmons. Dimensionality Reduction for Trajectory Learning from Demonstration, In Proceedings of IEEE InternationalConference on Robotics and Automation, May 2010

Motevallian, S.A., Yu, C. and Anderson, B.D.O., Robustness to the loss of multiple nodes in the localization of sensor networks, IFAC WorldCongress 2011, Milano

Ng, S.C and Mao,G., Analysis of k-Hop Connectivity Probability in 2-D Wireless Networks with Infrastructure Support, IEEE Globecom

Ng,S.C. Zhang, W., Yang, Y. and Mao, G., Analysis of Access and Connectivity Probabilities in Vehicular Relay Networks, IEEE Journal onSelected Areas in Communications--Special Issue Vehicular Communications and Networks

Rosenbloom, P. S. (2010). Speculations on leveraging graphical models for architectural integration of visual representation and reasoning.Proceedings of the AAAI-10 Workshop on Visual Representations and Reasoning

Rosenbloom, P. S. (2010). Rethinking cognitive architecture via graphical models. Cognitive Systems Research. In press.

Rosenbloom, P. S. (2010). Combining procedural and declarative knowledge in a graphical architecture. Proceedings of the 10thInternational Conference on Cognitive Modeling (ICCM 2010).

Rosenbloom, P. S. (2010). Implementing first-order variables in a graphical cognitive architecture. Biologically Inspired Cognitive

Architectures: Proceedings of the First Annual Meeting of the BICA Society. Arlington, VA: IOS Press.

Rosenbloom, P. S. (2010). An architectural approach to statistical relational AI. Proceedings of the AAAI-10 Workshop on StatisticalRelational AI.

Rosenbloom, P. S. (2010). Towards a new generation of cognitive architectures. Proceedings of the 2nd International Conference onAdvanced Intelligence. Abstract only. Stuckey, Peter J.. Lazy clause generation: Combining the power of SAT and CP (and MIP?)solving, Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, 7th InternationalConference, CPAIOR 2010, Bologna, Italy, June 14-18, 2010.


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Ruiz, N., Chen, F. and Oviatt S., Multimodal Input, in Multimodal Signal Processing: Theory and Applications for Human-ComputerInteraction. Edited by Thiran, J.P., Marques, F. and Bourlard, H., Elsevier, 2010, Chapter 12, pp. 231-255.

Shames, I., Deghat, M and Anderson B.D.O., Safe formation control and coordination with obstacle avoidance, IFAC World Congress 2011,Milano.

Yap, T. F., Ambikairajah, E., Epps, J. and Choi, E., Cognitive Load Classification Using Formant Features, Proc. IEEE InternationalConference on Information Sciences, Signal Processing and Their Applications (ISSPA10), Kuala Lumpur, Malaysia, May 2010, pp.221-224.

Yap, T. F., Epps, J., Choi, E. and Ambikairajah, E., Glottal Features For Speech-Based Cognitive Load Classification, Proc. IEEEInternational Conference on Acoustic, Speech and Signal Processing (ICASSP10), Dallas, USA, March 2010, pp. 5234-5237.

Yap, T. F., Epps, J., Ambikairajah, E. and Choi, E., An Investigation of Formant Frequencies for Cognitive Load Classification, Proc. AnnualConference of the International Speech Communication Association (InterSpeech10), Makuhari, Japan, September 2010, pp. 2022-

2025.

Yu, C., Dasgupta, S. and Anderson, B.D.O., Network localizability with link/node losses, IEEE CDC 2010

Yu, C., Dasgupta, S. and Anderson, B.D.O., Redundant localizability of sensor networks, SIAM Discrete Math

Yu, K., Epps, J. and Chen, F., Cognitive Load Evaluation of Handwriting Using Stroke-level Features, Proc. International Conference on

Intelligent User Interfaces (IUI11), Palo, Alto, U.S.A., February 2011, to appear.

Zarjam, P., Epps, J. and Chen F., Evaluation of Working Memory Load using EEG Signals, Proc. APSIPA Annual Summit and Conference(APSIPA 10), Biopolis Singapore, December 2010, to appear.

Zhang, Z., Mao, G., and Anderson, B.D.O., On the Information Propagation Speed in Mobile Vehicular Ad Hoc Networks, IEEE GlobecomZhang, Z, Ng, S.C., Mao, G. and Anderson, B. D. O., On the k-hop partial connectivity of finite wireless multi-hop networks, IEEE ICC 2011

Zhang, Z., Mao, G. and Anderson, B.D.O., On the Information Propagation Process in Mobile Vehicular Ad Hoc Networks, IEEETransactions on Vehicular Technology

Zhang, Z., Mao, G and Anderson, B.D.O., On the hop count statistics in wireless multi-hop networks subject to fading, IEEE Transactions onVehicular Technology

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8. Atkinson - AOARD Information Sciences