United States

Autonomous systems, both cyber and physical, operate in highly contested environmentsin which it must be assumed that adversaries are capable, agile and informed about state-of-the-arttechnology. In order to sustain performance in such environments, systems must be able to adaptautonomously through online machine learning - that is, improve their performance quickly, evenover the duration of a single engagement. In this presentation, we outline the challenges of adapting insuch environments and propose a solution approach that leverages a variety of recent innovations inreinforcement learning, distributed computing and trusted consensus algorithms such as Blockchain. We argue that multi-component systems operating in contested environments must leverage theirredundancy for learning while also remaining resilient with respect to component failures and com-promises. In particular, to enable and accelerate learning, such systems will have to allow somenumber of components to operate sub-optimally to achieve the right exploration-exploitation bal-ance needed for rapid and effective reinforcement learning. At the same time that some number ofcomponents are possibly being sacrificed due to sub-optimal performance, the underlying missionof the system must be maintained. This leads to challenges in distributed trusted computing suchas Byzantine agreement problems. We include a discussion of the role of current Blockchain tech-nology in supporting future multiagent adaptive adversarial autonomy with the desired associatedresilience.

NAML 2021

Resilient Distributed Adaptive Cyber-Defense Using Blockchain

regret minimization

upper confidence bounds

multiagent reinforcement learning

adaptive cyber-defense

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-23 is the Thirty-Seventh AAAI Conference on Artificial Intelligence. The theme of this conference is to create collaborative bridges within and beyond AI. Like previous AAAI conferences, AAAI-23 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and two new activities: a Bridge Program and a Lab Program. Many of these activities are tailored to the theme of bridges and all are selected according to the highest standards, with additional programs for students and young researchers.<br><br><br>
AAAI is providing you with a conference planner, which you can use to help organize your itinerary of activities.  This includes talks to attend in person, talks to attend remotely, breaks with colleagues  and your site seeing activities. To access this conference planner, please go to [https://aaai-2023.takemobi.io](https://aaai-2023.takemobi.io).<br><br><br><br>

In order to access this site, you need to register. If you haven't already, please register [here](https://aaai.org/Conferences/AAAI-23/registration/).


AAAI 2023

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines.

technical paper

Naval Information Warfare Center Pacific is partnering with AFCEA San Diego chapter to host the workshop.

The NAML workshop is an opportunity for researchers from Navy research and development centers and our partner organizations to exchange technical ideas and to come together as a team.

The goals of NAML are:

* To spread awareness of current machine learning research relevant to Naval applications

* To connect machine learning researchers with experts in military requirements

* To build and strengthen collaborations within the defense research community

**Watch this video to hear about the AFCEA purpose.**

<iframe width=1280 height=706 frameborder="0" scrolling="no" src="https://screencast-o-matic.com/player/creleVVcvRh?v=6&ff=1&title=0&controls=1" allowfullscreen="true"></iframe>

The Strategic and Technical Landscape in 2021

Leading Change and Transformation at Scale in an Era of AI and Exponential Technologies

Unlocking Power of Data for Space Exploration

Managing Emerging Technology Transitions

Keynote Q&A sessions

Autonomy and Edge Computing Q&A Session

Cyber Security Q&A Session

Data and analytics are strategic assets supporting the Department of the Navy’s DON Information Superiority Vision (ISV). Exploiting our data drives the critical insights and decision-making that inform the full range of DON missions and functions, from integrated joint operations to the care and feeding of the Naval enterprise. This session will discuss how Sailors, Marines, and Civilians are leveraging Jupiter, the Naval Enterprise Data & Analytics environment, to integrate, share, and exploit data at speed and scale across the Warfighting, Business, and Readiness pillars. Jupiter makes DON data widely discoverable, accessible, understandable, and usable across the Naval enterprise and arms our military and civilian decision-makers with decision support analytics and context-rich visualizations, while simultaneously providing our data workforce with access to advanced data tools. This session will focus on how four Naval organizations are leveraging Jupiter’s capabilities for data analysis, visualization, and advanced analytics to drive decision advantage.

Leveraging Jupiter for Decision Advantage Across the Department of the NavyDepartment of the Navy

Safety represents a primary consideration and formidable challenge for unmanned autonomous vehicles.   DoD Standard Practice for System Safety (MIL-STD-882E, 2012), and DoD Joint Software Systems Engineering Handbook (JSSSEH, 2012) provide standard practices and guidelines that can be applied to development, testing, and evaluation of software in unmanned autonomous systems.

This presentation highlights the process for software engineering and hazard analysis applicable to autonomous systems based on MIL-STD-882 and JSSSEH.  This process is broadly defined in terms of requirements, design, implementation, testing, verification, validation and lifecycle support tasking. 

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Next from NAML 2021

The Strategic and Technical Landscape in 2021

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Optimism in Face of a Context:Regret Guarantees for Stochastic Contextual MDP

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