Computational Methods for Decision Making | Apply Online

Opportunity Summary:

The Office of Naval Research (ONR) grant opportunity titled Computational Methods for Decision Making (Funding Opportunity Number ONRBAA14-010) supports applied research at the 6.2 level aimed at advancing the algorithms, methods, and software foundations behind automated decision support for naval missions. The central goal is to create and mature computational approaches that let autonomous information processing systems make rapid, accurate, and secure decisions in complex, time-varying environments. These systems are expected to exploit many kinds of inputs at once, including heterogeneous sensor feeds and open-domain or open-source data, and to do so under real operational constraints like uncertainty, incomplete or contradictory information, data latency, and distributed networked implementations. A major emphasis is not only on smarter decision logic, but also on demonstrating measurable performance and building trustworthy, high-performance implementations that are resilient and defect-resistant.

The opportunity is framed around the reality that decision quality depends on both the quality of underlying data and the trustworthiness of the computing environment that stores, processes, and transmits it. ONR highlights mission context as a key enabler: a system needs mission-driven hypotheses and models to decide what data matters, how to interpret it, and how uncertainty should propagate into inferences and choices. Because naval situational awareness often hinges on understanding what is known, how well it is known, and what remains unknown, the program also emphasizes strategies for identifying information gaps and directing new collection to improve the operational picture. In practical terms, that means automated systems that can sense, interpret, reason, and act in an open world while also validating existing models, revising assumptions, and generating new hypotheses when evidence demands it. The longer-term vision aligns with operational concepts such as persistent tactical surveillance and adaptive tasking across collection, processing, exploitation, and dissemination, with autonomy used to compress decision timelines.

ONR organizes the research into four coordinated thrust areas. The Resource Optimization thrust focuses on mathematically rigorous methods, especially optimization techniques, to produce optimal or provably near-optimal solutions to resource allocation problems that appear in naval planning and execution. Two highlighted themes are maritime mission planning, which targets better utilization and scheduling of expensive naval assets to improve power projection and operational efficiency, and sensor management and allocation, which targets optimal tasking and retasking of large sensor networks based on the evolving situation and sensor availability to maintain dynamic, persistent surveillance. Across both themes, the desired outputs are new optimization models and algorithms that can be turned into practical automated decision aids.

The Automated Image Understanding thrust aims to improve how machines interpret imagery and video in operationally relevant settings, with an emphasis on principled approaches that help explain and predict performance for system engineering. Priority topics include fusing multiple imaging modalities using the physics of image formation to improve enhancement and recognition; integrating images from multiple platforms for stronger object recognition, scene modeling, and change detection; indexing and retrieving imagery by semantic content; detecting and tracking objects on water or in urban environments (including real-time detection of partially occluded objects in clutter) and inferring potential threat; and building robust recognition systems that combine low-level vision with higher-level knowledge using generative and discriminative models. ONR also points to the importance of domain knowledge for reasoning over imagery, including applied research into visual knowledge bases and representations for high-level semantics such as context, background models, shape and appearance, behavior, and relationships among entities.

The Information Integration thrust addresses the fusion and interpretation of high-dimensional, multi-source datasets to produce coherent, actionable understanding. It emphasizes theoretically sound and consistent algorithms for organizing and structuring data, aligning and merging disparate sources, interpreting fused outputs, and estimating the value of information including the operational cost of missing data. The scope explicitly includes image and video, structured databases, social and complex networks, hyperspectral and multispectral data, acoustic and sensor-array data, and other structured sources. Key technical issues include turning unstructured data into usable structure that supports matching, search, outlier detection, learning, classification, query answering, reasoning, and decision making; building automated fusion methods that can handle uncertainty, incompleteness, imprecision, and contradictions; and developing ways to assess the quality of the fused battle-space picture and understand how that quality impacts downstream decisions.

The Cyber Security thrust recognizes that even the best decision algorithms are compromised if the software implementing them is vulnerable or unreliable. This thrust seeks a development environment and supporting methods that improve robustness and security with minimal performance overhead, tackling common implementation flaws such as buffer and stack/heap overflows, dangling pointers, input format violations, and race conditions. While formal verification has received significant attention, ONR stresses complementary approaches that make secure, correct implementation more likely in the first place. A distinctive idea here is tooling that captures and documents programmers design decisions and assumptions in real time during coding, because these decisions often shape security and correctness yet are frequently lost. By automatically recording workflow and intent and providing feedback during development, such tools could improve maintainability, reduce vulnerabilities, and increase developer productivity while strengthening trust in mission software.

Administratively, the opportunity was posted July 31, 2014 (created August 6, 2014) by the Office of Naval Research under CFDA 12.300 (Basic and Applied Scientific Research). It anticipated around 10 awards with an estimated total funding level of $7.5 million. The instrument types listed include grants and procurement contracts, cost sharing was not required, and eligibility was described as unrestricted (open to any entity type, subject to any specific eligibility language in the announcement). The original and current closing date were October 9, 2014, with white paper timing governed by the BAA instructions, and the archive date was November 8, 2014. For access issues, the notice listed a contract specialist contact and pointed applicants to the broader ONR BAA resources for full details and submission instructions.

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