AFOSR - Information and Networks

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Information and Networks (RTA2)
The Information and Networks Team within the Engineering and Information Science Branch is organized to support many U.S. Air Force priority areas including autonomy, space situational awareness, and cyber security. The research programs within this team lead the discovery and development of foundational issues in mathematical, information and network oriented sciences. They are organized along three themes: Information, Decision Making, and Networks.
The information theme addresses the critical challenges faced by the U.S. Air Force which lie at the intersection of the ability to collect, mathematically analyze, and disseminate large quantities of information in a time critical fashion with assurances of operation and security.
Closely aligned with the mathematical analysis of information is the need for autonomous decision making. Research in this theme focuses on the discovery of mathematical laws, foundational scientific principles, and new, reliable and robust algorithms, which underlie intelligent, mixed human-machine decision-making to achieve accurate real-time projection of expertise and knowledge into and out of the battle space.
Information analysis and decision making rarely occur in the context of a single source. The networks theme addresses critical issues involving how the organization and interaction among large collections of information providers and consumers contributes to an understanding of the dynamics of complex information systems.
The Information and Networks (AFOSR/RTA2) Program Officers and topics are:


Computational Cognition and Machine Intelligence

Program Description: This program supports innovative basic research on the fundamental principles and methodologies needed to enable intelligent machine behavior in support of autonomous and mixed-initiative (i.e., human-machine teaming) systems. The overall vision of this program is that future computational systems will achieve high levels of performance, adaptation, flexibility, self-repair, and other forms of intelligent behavior in the complex, uncertain, adversarial, and highly dynamic environments faced by the U.S. Air Force. This program covers the full spectrum of computational and machine intelligence, from cognitively plausible reasoning processes that are responsible for human performance in complex problem-solving and decision-making tasks, to non-cognitive computational models of intelligence necessary to create robust intelligent autonomous systems. Robustness in this context is the ability to achieve high performance given at least some or all of the following factors: uncertainty, incompleteness or errors in knowledge; limitations on sensing; real-world complexity and dynamic change; adversarial factors; unexpected events including system faults; and out-of-scope requirements on system behavior. In the midst of this spectrum are the technologies needed to seamlessly incorporate intelligent computational systems into mixed human-machine teams. The program is divided into three sub-areas that span the full spectrum of computational and machine intelligence. They are: Computational Cognition, Human-Machine Teaming, and Machine Intelligence.

The program encourages cross-disciplinary teams with collaboration including computer scientists, neuroscientists, cognitive scientists, mathematicians, statisticians, operation and management science researchers, information scientists, econometricians and game theoreticians, etc., especially when the research pertains to common issues and when collaboration is likely to generate bidirectional benefits. This program is aggressive, accepts risk, and seeks to be a pathfinder for U.S. Air Force research in this area. Proposals that may lead to breakthroughs or highly disruptive results are especially encouraged.

Basic Research Objectives: The Computational Cognition sub-area supports innovative basic research on high-order cognitive processes that are responsible for good human performance in complex problem solving and decision making tasks – we only want to model the things people excel at. The sub-area also seeks to support research on building computational systems that derive from and/or integrate cognitive and biological models of human and animal intelligence. The overall objective is to understand and exploit these processes to create computational models that perform as well as or better than the reasoning systems they emulate.
This sub-area seeks basic research to elucidate core computational approaches that pertain to exploiting the capabilities of the mind and brain (human or animal) for creating more intelligent machines, as well as cognitively plausible mechanisms inspired by human (or animal) reasoning. In relating formal models to human cognition and performance, research projects should not only ascertain their descriptive validity but also their predictive validity. To this end, the program welcomes work that (1) creates cognitively plausible computational frameworks that semi-autonomously integrates model development, evaluation, selection, and revision; and (2) bridges the gap between the fields of cognitive modeling and artificial general intelligence by simultaneously emphasizing important improvements to functionality and also explanatory evaluation against specific empirical results. The program also encourages the development and application of novel and innovative mathematical and neurocomputational approaches to tackle the fundamental mechanisms of the brain, that is, how cognitive behavior emerges from the complex interactions of individual neurobiological systems and neuronal circuits.

The Human-Machine Teaming sub-area is concerned with the need for mixed human-machine decision making, which appears at all levels of U.S. Air Force operations and pervades every stage of U.S. Air Force missions. To that end, new theoretical and empirical guidance is needed to prescribe maximally effective mixtures of human and machine decision making in environments that are becoming increasingly complex and demanding as a result of the high uncertainty, complexity, time urgency, and rapidly changing nature of military missions. New computational and mathematical principles of cognition are needed to form a symbiosis between human and machine systems, which coordinates and allocates responsibility between these entities in a collaborative manner, achieving comprehensive situation awareness and anticipatory command and control.
This sub-area seeks new empirical and theoretical basic research that provides a deeper understanding of the cognitive requirements of a decision maker with enhanced capability for situation awareness, allows for greater degree of uncertainty in terms of reasoning systems, produces greater robustness and adaptability in dealing with unexpected interruptions and rapidly changing objectives, generates greater flexibility in terms of assumptions about adversarial agents, and gives clearer guidance for dealing with the complexities encountered in network-centric decision tasks.

The Machine Intelligence sub-area supports innovative basic research on fundamental principles and methodologies of computational intelligence necessary to create robust intelligent autonomous systems. These methodologies are likely to be non-cognitive, taking full advantage of the strengths embodied in mathematical and computational systems, such as the ability of quickly manage vast amounts of data.
This sub-area encourages research enabling the creation of computational systems that embody intelligent behavior based on less-strict cognitive or purely mathematical approaches. Proposals that lead to advances in the basic principles of machine intelligence for memory, reasoning, (non-statistical) learning, action, and communication are desired insofar as these contribute directly towards robustness as defined above. Research proposals on computational reasoning methodologies of any type and combination, including algorithmic, heuristic, or evolutionary, are encouraged as long as the proof of success is the ability to act autonomously or in concert with human teammates to achieve robustness as defined above. Computational intelligence systems often act as human intelligence amplifiers in such areas as planning, sensing, situation assessment and projection; will monitor, diagnose, and control aircraft or spacecraft; and will directly interact with humans and the physical world through robotic devices. Therefore, research that that enables mixed-initiative interaction and teaming between autonomous systems and human individuals or teams is an important part of the program.

You are highly encouraged to contact our Program Officer prior to developing a full proposal to briefly discuss the current state-of-the-art, how your research would advance it, and the approximate cost for a three (3) to five (5) year effort.

DR. JAMES H. LAWTON, AFOSR/RTA2
Email:
machine.itel@us.af.mil

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Computational Mathematics

Program Description: This program seeks to develop innovative mathematical methods and fast, reliable and scalable algorithms aimed at making radical advances in computational science. Research in computational mathematics underpins the fundamental understanding of complex physical phenomena and leads to predictive simulation capabilities that are crucial to the design and control of future U.S. Air Force systems, and their lifetime expectancy. Proposals to this program should focus on fundamental scientific and mathematical innovations, and should have the potential to address some of the most important computational challenges in science and engineering. Additionally, it is desirable to frame the basic research ideas in the context of applications relevant to the U.S. Air Force, which can serve simultaneously to focus the research and to provide avenues for transition of basic research outcomes into practice. Applications of current Air Force interest include, but are not limited to; quantum physics, plasma dynamics, turbulence, lasers and directed energy, aero-thermo-dynamics, information science, data analysis, biophysics and material science.

Basic Research Objectives: Research under this program has traditionally emphasized schemes that address the discretization and numerical solution of complex systems of equations, generally partial differential equations derived from physical models. However, alternative computational approaches are also of interest, particularly in connection with emerging and multi-disciplinary applications, typically involving very high-dimensional and complex systems and/or mesoscale problems. Research areas of particular interest currently include innovative methods for: quantum many-body physics, especially strongly correlated systems and environmental interactions; non-equilibrium statistical processes and turbulent dynamics with multiple physical interactions and large parameter spaces; high-dimensional, non-linear system dynamics, including transport equations and inverse problems, including those on complex and evolving networks; self-organized criticality and rare and extreme events.  Traditional computational methods such as high-order spatial and temporal algorithms remain of interest, but to meet the formidable computational challenges associated with current and future problems of interest to the U.S. Air Force, a wide spectrum of numerical methods must be developed and improved within the scope of this program. Increased emphasis is placed on approaches that can handle a very high number of dimensions, uncertainty and stochasticity for non-Markovian processes, far from equilibrium conditions, and/or a wide range of scales (e.g. space, time, physical parameters, or complexity). Such approaches include, but are not limited to: deterministic and stochastic reduced-order models, dimensionality reduction via projection or data-driven techniques, stochastic differential equations, mean-field games, path-integrals, Mori-Zwanzig projection, duality, fractional differential equations, and hybrid methods. All proposed methods must have quantifiable measures of fidelity, efficiency and adaptivity, based on rigorous analysis and preferably demonstrated on canonical challenge and grand-challenge problems. An additional area of interest is the investigation of new paradigms and revolutionary concepts of computing, outside of quantum algorithms, that go beyond the incremental improvements offered by large-scale parallelization, for both deterministic and stochastic problems; such approaches may include for example, analog and/or physical surrogates.

You are highly encouraged to contact our Program Officer prior to developing a full proposal to briefly discuss the current state-of-the-art, how your research would advance it, and the approximate cost for a three (3) to five (5) year effort.

DR. JEAN-LUC CAMBIER, AFOSR/RTA2
E-mail:
comp.math@us.af.mil

 

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Dynamics and Control                

Program Description: This program emphasizes the interplay of dynamical systems and control theories with the aim of developing innovative synergistic strategies for the design and analysis of controlled systems that enable radically enhanced capabilities, including performance and operational efficiency for future U.S. Air Force systems. Proposals should focus on the fundamental science and mathematics first, but should also include connectivity to appropriate Air Force applications of the future. These applications currently include information systems, as well as autonomous/semi-autonomous aerial vehicles, munitions, and space vehicles. The dramatic increase in complexity of Air Force systems provides unique challenges for the Dynamics and Control Program. Meeting these challenges may require interdisciplinary approaches as well as deeper studies within single disciplines. Lastly, note that the Dynamics and Control Program places special emphasis on mathematically rigorous techniques addressing realistic treatment of applications, complexity management, semi-autonomous systems, and real-time operation in stochastic and adversarial environments.

Basic Research Objectives: Current research interests include: methods of dynamical analysis of complex systems for the purpose of real-time control, control of ensemble and infinite dimensional systems, real-time reachability set calculation, real time verification and validation of hybrid systems, distributed and decentralized decision making and control for coordinated autonomous/semi-autonomous aerospace vehicles considering constraints, uncertain, information rich, dynamically changing, networked environments; understanding how to optimally account for humans in the design space; novel schemes that enable challenging multi-agent aerospace tracking in complex, cluttered scenarios; robust and adaptive non-equilibrium (e.g., set-based) control of nonlinear processes where the primary objective is enhanced operability rather than just local stability; new methods for understanding and mitigating the effects of uncertainties in dynamical processes where uncertainty distribution is non-Gaussian; novel hybrid control systems that can intelligently manage actuator, sensor, and processor communications in a complex, spatially distributed and evolving system of systems; sensor rich, data driven adaptive control; and applying control concepts motivated by studies of biological systems. In general, interest in the control of large complex, multi-scale, hybrid, highly uncertain nonlinear systems is increasing. Further, new mathematics in clear support of dynamics and control is of fundamental importance.

In this regard, some areas of interest include, but are not limited to, hybrid dynamical systems theory, geometric and algebraic methods of dynamics and control, stochastic and adversarial systems, control of cyber physical systems, emerging areas of control theory, graph theoretic control theory over nonlinear dynamics, partial and corrupted information, max-plus and idempotent methods, nonlinear control and estimation, and novel computational techniques specifically aimed at control of systems with large data.

You are highly encouraged to contact our Program Officer prior to developing a full proposal to briefly discuss the current state-of-the-art, how your research would advance it, and the approximate cost for a three (3) to five (5) year effort.

DR. FREDERICK LEVE, AFOSR/RTA2
E-Mail:
dycontrol@us.af.mil

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Dynamic Data Driven Applications Systems (DDDAS)
            

Program Description: The DDDAS concept entails the ability to dynamically incorporate additional data into an executing application, and in reverse, the ability of an application to dynamically steer the measurement (instrumentation and control) components of the application system. DDDAS is a key concept for improving modeling of systems under dynamic conditions, more effective management of instrumentation systems, and is a key concept in architecting and controlling dynamic and heterogeneous resources, including, sensor networks, networks of embedded controllers, and other networked resources. DDDAS transformative advances in computational modeling of applications and in instrumentation and control systems (and in particular those that represent dynamic systems) require multidisciplinary research, and specifically need synergistic and systematic collaborations between applications domain researchers with researchers in mathematics and statistics, researchers computer sciences, and researchers involved in the design/ implementation of measurement and control systems (instruments, and instrumentation methods, and other sensors and embedded controllers). 

Basic Research Objectives: Individual and multidisciplinary research, technology development, and cyber Infrastructure software frameworks needed for DDDAS applications and their environments are sought, along four key science and technology frontiers: Applications modeling: In DDDAS an application/simulation must be able to accept data at execution time and be dynamically steered by such dynamic data inputs. This requires research advances in application models that: describe the application system at different levels of detail and modalities; are able to dynamically invoke appropriate models as needed by the dynamically injected data into the application; and include interfaces of applications to measurements and other data systems. DDDAS will, for example, engender an integration of large scale simulation with traditional controls systems methods, thus provide an impetus of new directions to traditional controls methods. Advances in Mathematical and Statistical Algorithms include creating algorithms with stable and robust convergence properties under perturbations induced by dynamic data inputs: algorithmic stability under dynamic data injection/streaming; algorithmic tolerance to data perturbations; multiple scales and model reduction; enhanced asynchronous algorithms with stable convergence properties; multimodal, multiscale modeling and uncertainty quantification, and in cases where the multiple scales or modalities are invoked dynamically and there is need for fast methods of uncertainty quantification and uncertainty propagation across dynamically invoked models. Such aspects push to new levels of challenges the traditional computational math approaches. Application Measurement Systems and Methods include improvements and innovations in instrumentation platforms, and improvements in the means and methods for collecting data, focusing in a region of relevant measurements, controlling sampling rates, multiplexing, multisource information fusion, and determining the architecture of heterogeneous and distributed sensor networks and/or networks of embedded controllers. The advances here will create new instrumentation and control capabilities. Advances in Systems Software runtime support and infrastructures to support the execution of applications whose computational systems resource requirements are dynamically dependent on dynamic data inputs, and include: dynamic selection at runtime of application components embodying algorithms suitable for the kinds of solution approaches depending on the streamed data, and depending on the underlying resources, dynamic workflow driven systems, coupling domain specific workflow for interoperation with computational software, general execution workflow, software engineering techniques. The systems software environments required are those that can support execution in dynamically integrated platforms ranging from the high-end to the real-time data acquisition and control - cross-systems integrated. Software Infrastructures and other systems software (OS, data-management systems and other middleware) services to address the “real time” coupling of data and computations across a wide area heterogeneous dynamic resources and associated adaptations while ensuring application correctness and consistency, and satisfying time and policy constraints. Specific features include the ability to process large volume, high rate data from different sources including sensor systems, archives, other computations, instruments, etc.; interfaces to physical devices (including sensor systems and actuators), and dynamic data management requirements.

Areas of interest to the AF and which can benefit from DDDAS transformative advances, include areas driven by the AF Technology Horizons, Energy Horizons, and Global Horizons reports, such as: autonomous systems (e.g. swarms of unmanned or remotely piloted vehicles); autonomous mission planning; complex adaptive systems with resilient autonomy; collaborative/cooperative control; autonomous reasoning and learning; sensor-based processing; ad-hoc, agile networks; multi-scale simulation technologies and coupled multi-physics simulations; decision support systems with the accuracy of full scale models (e.g. high-performance aircraft health monitoring, materials stresses and degradation); embedded diagnostics and V&V for complex adaptive systems; automated software generation; cognitive modeling; cognitive performance augmentation; human-machine interfaces. DDDAS provides new approaches for combining computational, theoretical, and instrumentation data sets for high interactive testing of multiple physical and engineering hypotheses.

Programmatic activities that will be launched under this initiative will support research in individual areas, but mostly in the context of multidisciplinary research across at least two of the four components under Basic Area Objectives above.

You are highly encouraged to contact our Program Officer prior to developing a full proposal to briefly discuss the current state-of-the-art, how your research would advance it, and the approximate cost for a three (3) to five (5) year effort.

DR. ERIK PL. BLASCH, AFOSR/RTA2
E-mail:
dddas@us.af.mil

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Information Assurance and Cybersecurity
               

Program Description: Securing cyberspace, defending against and preventing cyber attacks are not new but have become increasingly pressing in the light of technological advancements.  Software and protocols are only becoming more complex to meet application demands.  More flexible computing environments such as distributed systems need new ways of thinking to ensure secure end-to-end functionalities even though components are only known to be individually secure.  The emergence of nanoscale devices and quantum information processing and communication portends new technological challenges for cybersecurity.  By the same token, these new technologies potentially offer unparalleled security solutions to the existing or future problems.

Although engineering practices continue to provide short-term and temporary relieves to these pressing needs, new scientific ideas are required to address insecurity and hostility in cyberspace, especially, taking into account of emerging technologies.  Many fundamental concepts are still eluding precise formulation and awaiting rigorous responses.  The goal of this Basic Research program is to explore novel, promising concepts and methodologies that can establish a firm scientific foundation for cybersecurity and potentially tackle the difficult technical hurdles put forth in the previous paragraph.  

Basic Research Objectives: Recent developments and advances in the following research areas of computer science and mathematics are expected to provide valuable insights into various cybersecurity problems: dependent type theory, cryptographic protocols for interactive computation and communication, interactive and automated theorem proving, language-based techniques in software and hardware for formal specification and verification, secure protocols, game theory with strong security content, obfuscation and fully homomorphic encryption, model categories, formalized mathematics.  Broadly speaking, cross-fertilization of mathematical formalisms and logical constructs will likely continue to play a central role in the construction and verification of security invariants, and in the study of security models or security principles. 

These scientific advances are expected to contribute fresh ideas to a number of fundamental cybersecurity topics: composition of security properties and protocols in distributed interactive systems without the need of trusted third parties; rigorous techniques to enable persistent and secure operations on unsecure or untrusted systems; information flow security and noninterference in dynamic and distributed settings; new security invariants that can readily be computed and interpreted, especially for systems endowed with rich geometric dynamics; rigorous proofs and construction of obfuscation techniques for programs and circuits to enhance security; formal verification and certification of the correctness of complex large-scale mathematical proofs and critical computer systems.

Aside from software and secure protocols, nanoscale material properties and quantum effects should offer added security capabilities for future computing devices that cannot be realized by today’s technologies. They potentially enable physical construction of cryptographic primitives that are traditionally described by algorithms and typically implemented by software.  Random Number Generators and Physical Unclonable Functions are simplest examples of such construction. At the same time, securing future unconventional technologies will require the introduction of new security principles and security models that may substantially deviate from the traditional approaches.  In fact, various concepts in quantum information science and quantum computation such as quantum resources (entanglement, non-locality, contextuality, etc.) and quantum computational complexity are highly relevant to security of future communication and computing systems in which classical and quantum devices interact.

Research areas of interest to this program include, but are not limited to, the methodologies and topics described above.  Highest priority will be given to projects with novel scientific ideas that potentially deliver new DoD/Air Force capabilities.

You are highly encouraged to contact our Program Officer prior to developing a full proposal to briefly discuss the current state-of-the-art, how your research would advance it, and the approximate cost for a three (3) to five (5) year effort.

DR. TRISTAN N. NGUYEN, AFOSR/RTA2
E-mail:
info.security@us.af.mil

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Optimization and Discrete Mathematics

Program Description: The program goal is the development of mathematical methods for the optimization of large and complex models that will address future decision problems of interest to the U.S. Air Force. Areas of fundamental interest include resource allocation, planning, logistics, engineering design and scheduling. Increasingly, the decision models will address problems that arise in the design, management and defense of complex networks, in robust decision making, in performance, operational efficiency, and optimal control of dynamical systems, and in artificial intelligence and information technology applications.

Basic Research Objectives:
There will be a focus on the development of new nonlinear, integer and combinatorial optimization algorithms, including those with stochastic components. Techniques designed to handle data that are uncertain, evolving, incomplete, conflicting, or overlapping are particularly important.
As basic research aimed at having the broadest possible impact, the development of new computational methods will include an emphasis on theoretical underpinnings, on rigorous convergence analysis, and on establishing provable bounds for (meta-) heuristics and other approximation methods.

You are highly encouraged to contact our Program Officer prior to developing a full proposal to briefly discuss the current state-of-the-art, how your research would advance it, and the approximate cost for a three (3) to five (5) year effort.

We are currently searching/hiring a new Program Officer, but there is a temporary custodian until a new PO is selected. Emails sent to the email address below will go to the temporary custodian:

(ACTING) DR. JEAN-LUC CAMBIER, AFOSR/RTA2
E-Mail:
odmath@us.af.mil

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Science of Information, Computation, Learning, and Fusion

Program Description: The U.S. Air Force collects vast amounts of data through various modes at various times in order to extract and derive needed “information” from these large and heterogeneous (mixed types) data sets. Some data, such as those collected from magnetometers, register limited information content which is more identifiable at the sensor level but beyond human’s sensory reception. Other types of data, such as video cameras or text reports, possess more semantic information that is closer to human cognition and understanding. Nevertheless, these are instances of disparate data which encapsulate different types of “information” pertained to, perhaps, the same event(s) captured by different modalities through sensing and collection.

In order to understand and interpret information contained in various data sources, it is necessary to extract relevant pieces of information from these datasets and to make inferences based on prior knowledge and probabilities. This bottom-up processing direction needs conceptually driven reasoning to integrate or fuse the previously extracted snippets of information by leveraging domain knowledge. Furthermore, the top-down processes can offer causal explanation or causal inference, generate new hypotheses, verify or test hypotheses in light of observed datasets. Between the data-driven and conceptually-driven ends, there may reside different levels of abstraction in which information is partially extracted and aggregated based on the nature of applications.

Basic Research Objectives:
With the rationale and guiding principles outlined in the above paragraph, this program seeks fundamental research that potentially leads to scientific advancements in informatics, computation, and learning that can support processing and making sense of complex disparate information sources. After all, information processing can formally and fundamentally be described as computing and reasoning on various knowledge representations. Successes in addressing the research sub-areas stated below would give the U.S. Air Force new capabilities to:
(1) shift emphasis from sensing to information awareness; (2) understand the underpinning of autonomy; (3) relieve human’s cognitive overload in dealing with the data deluge problem; (4) enhance human-machine interface in information processing.
To accomplish the research objectives, this program focuses on, but is not limited to, new techniques in mathematics, computing science, statistics and logic which have potentials to: (1) cope with various complex disparate data/information types; (2) integrate a diversity of unique reasoning and learning components collaborating simultaneously (e.g., multi-strategy reasoning and learning); (3) bridge correlational with causal discovery; (4) determine solutions or obstructions to local-to-global data-fusion problems; (5) mechanize reasoning/learning and computing in the same computational environment; (6) yield provably efficient procedures to enable or facilitate data analytics; (7) deal with high-dimensional and massive datasets with provably guaranteed performance.

You are highly encouraged to contact our Program Officer prior to developing a full proposal to briefly discuss the current state-of-the-art, how your research would advance it, and the approximate cost for a three (3) to five (5) year effort.

DR. RICHARD D. (DOUG) RIECKEN, AFOSR/RTA2
E-mail:
icf@us.af.mil

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Systems and Software

Program Description: The AF’s mission is to “fly, fight, and win in air, space, and cyberspace.” In order to accomplish its mission, the AF invests in Systems & Software, which is the keystone of all advanced technology. The Systems & Software program actively searches for ideas with respect to two submissions: 1) Improving current AF systems, and; 2) Introducing cutting-edge research to expand the field of knowledge. Improving current AF systems is needed; the AF’s use of legacy systems is well known, along with the detrimental issues of legacy system use. There are many AF systems which have extremely long life cycles (such as combat system software). In order to ensure that these legacy systems are up-to-date, new systems infrastructures are investigated. Additionally, new areas of Systems & Software are encouraged to ensure that the AF continues to be on the cutting-edge of technology; novel areas include entirely new directions that will have significant impact in the future. Overall examples of areas include operating systems, compilers, virtual memory, multi-core platforms, etc. AFOSR is looking for research that will drastically improve current AF systems and help to develop new S&T for the benefit of the nation.

Basic Research Objectives: As stated above, Systems & Software addresses two issues – both the new and the old: 1) New Technology Research (such as, but not limiting to, multi-core and many-core systems), and; 2) Legacy System Research (concerning existing AF systems such as, but not limiting to, operating systems, software, etc.). Since Systems & Software direction is continually changing, i.e., technology life-span of approximately 3 years or less, specific subareas are not specifically stated within this announcement; instead, due to the topical nature of the field, the specific area of research is open to the proposer, as long as the research addresses either issue – New Technology Research or Legacy System Research – in Systems & Software. Any new ideas of either of the two issues are welcomed.

You are highly encouraged to contact our Program Officer prior to developing a full proposal to briefly discuss the current state-of-the-art, how your research would advance it, and the approximate cost for a three (3) to five (5) year effort.

(ACTING) DR. JAMES H. LAWTON, AFOSR/RTA2

E-mail: systems.software@us.af.mil

 

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Trust and Influence

Program Description:
The Trust and Influence program is motivated by recent technological advances in the area of unmanned and autonomous systems, and the strategic environment that the U.S. Air Force is expected to face in the future; a significant departure from that which has dominated most of its history. The Air Force is facing a broader range of threats that are less predictable, with many conflicts occurring in failed or failing states that include radical extremists and a wide range of non-state actors. Moreover, the rapid advances and proliferation of advanced autonomous systems are expected to fundamentally change the way the Air Force operates. To address these challenges, the Trust and Influence program invests in the development of the theoretical and empirical foundations of reliance and contemporary influence. Specifically, we are concerned with investigating the mechanisms by which humans establish, maintain, and repair trust in other agents, both human and machine. The science of influence or persuasion will expand our understanding for how we might shape the behaviors, attitudes and beliefs of others. The resulting portfolio directly enhances the Air Force's technology development programs, and will impact policies and operations related to national security. Trust and Influence invests in the discovery of the foundational concepts of effective influence, deterrence, trust-building, trust calibration, and counter-terrorism operations. Multi-disciplinary approaches are encouraged, to include cognitive science, neuroscience, anthropology, sociology, linguistics, economics, computer science and mathematics. Research designs that incorporate laboratory studies, modeling or field research leading to transformative novel theories are also encouraged.

Basic Research Objectives:
The basic research interests under this program can be defined broadly by three areas: trust in autonomous systems, cross-cultural trust, and socio-digital influence. In the area of trust in autonomous systems there is particular interest in (1) empirical studies to examine drivers of trust between humans and intelligent, autonomous or robotic agents, (2) laboratory and field studies to examine the impact of socially-designed cues or physical features such as appearance, voice, personality, and other social elements on human trust and system performance, (3) development of trust metrics and other relevant constructs in human-machine teaming with a particular focus on real-time and dynamic assessment, and (4) modeling of human-machine teaming that supports adaptive and continuous improvement of joint performance in complex environments. In the area of cross-cultural trust, there is interest in (1) developing theories of interpersonal and organization trust that account for various cultural constructs and characteristics, (2) revealing the antecedents of trust in cross-cultural interactions, and (3) cultural differences in complex human-machine interaction. In the area of socio-digital influence there is a need for (1) laboratory and field studies to reveal sources of influence and persuasion in social media and across different cultural groups, (2) social, cognitive, and neural mechanisms of influence and persuasion (3) modeling and measuring the relationship between online and real-world behaviors, (4) empirical studies to discover new theories of influence as it pertains to the cyber domain, and (5) understanding the behavioral effects of influence tactics such as foreign policies or developmental activities.

You are encouraged to contact our Program Officer prior to developing a full proposal to discuss alignment of your ideas with our program goals, your proposed methods, and the scope of your proposed effort.

DR. BENJAMIN A. KNOTT, AFOSR/RTA2
Email:
ti@us.af.mil

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