Distributed intelligent control and management (DICAM) applications and support for semi-automated development

We have recently begun a 4-year effort to develop a new technology foundation and associated methodology for the rapid development of high-performance intelligent controllers. Our objective in this work is to enable system developers to create effective real-time systems for control of multiple, coordinated entities in much less time than is currently required. Our technical strategy for achieving this objective is like that in other domain-specific software efforts: analyze the domain and task underlying effective performance, construct parametric or model-based generic components and overall solutions to the task, and provide excellent means for specifying, selecting, tailoring or automatically generating the solution elements particularly appropriate for the problem at hand. In this paper, we first present our specific domain focus, briefly describe the methodology and environment we are developing to provide a more regular approach to software development, and then later describe the issues this raises for the research community and this specific workshop

Puppetry vs. creationism: why AI must cross the chasm

Like the master puppet makers of the classic folktales, AI engineers have built some marvelous machines. These machines are surely valuable, but our puppetry won't cross the chasm separating us from a world of artificially intelligent creatures. To get there, we need a singularity of artificial creationism, where we launch aritficial beings that can adapt, learn and evolve. We need to emphasize the development of continously self-improving systems that interact with and perform tasks in the physical world. Creation of those systems will mark a singularity in the punctuated evolution of artificial intelligence

Executive redirection to agile IT methods: A proposed pilot effort to radically improve time to value. A credible way to move DoD forward from its traditional and failing IT ways (One-page memorandum, )

Unpublished, but freely shared

Truthiness Fever: How Lies and Propaganda are Poisoning Us and a Ten-Step Program for Recovery (Publication Announcement)

A publication announcement created for an event at the Dudley Knox Library, Naval Postgraduate Schoo

Architecture for Adaptive Intelligent Systems

We identify a class of niches to be occupied by 'adaptive intelligent systems (AISs)'. In contrast with niches occupied by typical AI agents, AIS niches present situations that vary dynamically along several key dimensions: different combinations of required tasks, different configurations of available resources, contextual conditions ranging from benign to stressful, and different performance criteria. We present a small class hierarchy of AIS niches that exhibit these dimensions of variability and describe a particular AIS niche, ICU (intensive care unit) patient monitoring, which we use for illustration throughout the paper. We have designed and implemented an agent architecture that supports all of different kinds of adaptation by exploiting a single underlying theoretical concept: An agent dynamically constructs explicit control plans to guide its choices among situation-triggered behaviors. We illustrate the architecture and its support for adaptation with examples from Guardian, an experimental agent for ICU monitoring

Hyper-Nodes for Emerging Command and Control Networks: The 8th Layer

11th International Command and Control Research and Technology Symposium (ICCRTS), September 26-28, 2006, Cambridge, U

Using action-based hierarchies for real-time diagnosis

AbstractAn intelligent agent diagnoses perceived problems so that it can respond to them appropriately. Basically, the agent performs a series of tests whose results discriminate among competing hypotheses. Given a specific diagnosis, the agent performs the associated action. Using the traditional information-theoretic heuristic to order diagnostic tests in a decision tree, the agent can maximize the information obtained from each successive test and thereby minimize the average time (number of tests) required to complete a diagnosis and perform the appropriate action. However, in real-time domains, even the optimal sequence of tests cannot always be performed in the time available. Nonetheless, the agent must respond. For agents operating in real-time domains, we propose an alternative action-based approach in which: (a) each node in the diagnosis tree is augmented to include an ordered set of actions, each of which has positive utility for all of its children in the tree; and (b) the tree is structured to maximize the expected utility of the action available at each node. Upon perceiving a problem, the agent works its way through the tree, performing tests that discriminate among successively smaller subsets of potential faults. When a deadline occurs, the agent performs the best available action associated with the most specific node it has reached so far. Although the action-based approach does not minimize the time required to complete a specific diagnosis, it provides positive utility responses, with step-wise improvements in expected utility, throughout the diagnosis process. We present theoretical and empirical results contrasting the advantages and disadvantages of the information-theoretic and action-based approaches

Event Processing in the Global Information Grid GIG): Orders of Magnitude Advantage in Information Supply Chains through Context-sensitive Smart Push VIRT

(2nd Event Processing Symposium, Oracle, Redwood Shores, CA

Valuing Persistent ISR Resources

AFCEA-GMU C4I Center Symposium, Challenges in C4I, George Mason University, Fairfax, VA., May 25This paper describes how to optimize PISR resources to maximize VIRT