Cooperative Behavior In ModSAF

Report on research into mechanisms for cooperative behaviors in computer generated forces

Proceedings, MSVSCC 2012

Proceedings of the 6th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 19, 2012 at VMASC in Suffolk, Virginia

Modeling human and organizational behavior using a relation-centric multi-agent system design paradigm

Today's modeling and simulation communities are being challenged to create rich, detailed models incorporating human decision-making and organizational behavior. Recent advances in distributed artificial intelligence and complex systems theory have demonstrated that such ill-defined problems can be effectively modeled with agent-based simulation techniques using multiple, autonomoous, adaptive entities. RELATE, a relation-centric design paradigm for multi-agent systems (MAS), is presented to assist developers incorporate MAS solutions into their simulations. RELATe focuses the designer on six key concepts of MAS simulations: relationships, environment, laws, agents, things, and effectors. A library of Java classes is presented which enables the user to rapidly prototype an agent-based simulation. This library utilizes the Java programming language to support cross-platform and web based designs. All Java classes and interfaces are fully documented using HTML Javadoc format. Two reference cases are provided that allow for easy code reuse and modification. Finally, an existing metworked DIS-Java-VRML simulation was modified to demonstrate the ability to utilize the RELATE library to add agents to existing applications. LCDR Kim Roddy focused on the development and refinement of the RELATE design paradigm, while LT Mike Dickson focused on the actual Java implementation. Joint work was conducted on all research and reference caseshttp://www.archive.org/details/modelinghumanorg00roddU.S. Navy (U.S.N.) author

The Need for An Australian Regulatory Code for the Use of Artificial Intelligence (AI) in Military Application

Artificial Intelligence (AI) is enabling rapid technological innovation and is ever more pervasive, in a global technological eco-system lacking suitable governance and absence of regulation over AI-enabled technologies. Australia is committed to being a global leader in trusted secure and responsible AI and has escalated the development of its own sovereign AI capabilities. Military and Defence organisations have similarly embraced AI, harnessing advantages for applications supporting battlefield autonomy, intelligence analysis, capability planning, operations, training, and autonomous weapons systems. While no regulation exists covering AI-enabled military systems and autonomous weapons, these platforms must comply with International Humanitarian Law, the Law of Armed Conflict, and the Use of Force. This paper examines comparative international regulatory approaches across major allied nations in the US, UK, and Europe and suggests future direction for Australian regulation of AI in lethal application

Cyborg rhetoric and revelation of self: Identity, writing, and the instantiation of the cyborg in digital texts

This thesis examines three digital texts and explores the ways writing, technology, and narratives embedded in popular culture reveal cyborg language

Disruptive Technologies with Applications in Airline & Marine and Defense Industries

Disruptive Technologies With Applications in Airline, Marine, Defense Industries is our fifth textbook in a series covering the world of Unmanned Vehicle Systems Applications & Operations On Air, Sea, and Land. The authors have expanded their purview beyond UAS / CUAS / UUV systems that we have written extensively about in our previous four textbooks. Our new title shows our concern for the emergence of Disruptive Technologies and how they apply to the Airline, Marine and Defense industries. Emerging technologies are technologies whose development, practical applications, or both are still largely unrealized, such that they are figuratively emerging into prominence from a background of nonexistence or obscurity. A Disruptive technology is one that displaces an established technology and shakes up the industry or a ground-breaking product that creates a completely new industry.That is what our book is about. The authors think we have found technology trends that will replace the status quo or disrupt the conventional technology paradigms.The authors have collaborated to write some explosive chapters in Book 5:Advances in Automation & Human Machine Interface; Social Media as a Battleground in Information Warfare (IW); Robust cyber-security alterative / replacement for the popular Blockchain Algorithm and a clean solution for Ransomware; Advanced sensor technologies that are used by UUVs for munitions characterization, assessment, and classification and counter hostile use of UUVs against U.S. capital assets in the South China Seas. Challenged the status quo and debunked the climate change fraud with verifiable facts; Explodes our minds with nightmare technologies that if they come to fruition may do more harm than good; Propulsion and Fuels: Disruptive Technologies for Submersible Craft Including UUVs; Challenge the ammunition industry by grassroots use of recycled metals; Changing landscape of UAS regulations and drone privacy; and finally, Detailing Bioterrorism Risks, Biodefense, Biological Threat Agents, and the need for advanced sensors to detect these attacks.https://newprairiepress.org/ebooks/1038/thumbnail.jp

Digital entrapment: tangible and intangible impact

The recent pandemic has had an impact not only on the health and economy of citizens but boosted the digital transition. This paper summarises some of the impacts due to the increasing use of digital solutions, the list of impacts included will simply provide an idea about some of the impacts, but they are not limited to this set

Implementing machine ethics: using machine learning to raise ethical machines

As more decisions and tasks are delegated to the artificially intelligent machines of the 21st century, we must ensure that these machines are, on their own, able to engage in ethical decision-making and behaviour. This dissertation makes the case that bottom-up reinforcement learning methods are the best suited for implementing machine ethics by raising ethical machines. This is one of three main theses in this dissertation, that we must seriously consider how machines themselves, as moral agents that can impact human well-being and flourishing, might make ethically preferable decisions and take ethically preferable actions. The second thesis is that artificially intelligent machines are different in kind from all previous machines. The conjunction of autonomy and intelligence, among other unique features like the ability to learn and their general-purpose nature, is what sets artificially intelligent machines apart from all previous machines and tools. The third thesis concerns the limitations of artificially intelligent machines. As impressive as these machines are, their abilities are still derived from humans and as such lack the sort of normative commitments humans have. In short, we ought to care deeply about artificially intelligent machines, especially those used in times and places when considered human judgment is required, because we risk lapsing into a state of moral complacency otherwise