Building an adaptive agent to monitor and repair the electrical power system of an orbital satellite

Over several years we have developed a multistrategy apprenticeship learning methodology for building knowledge-based systems. Recently we have developed and applied our methodology to building intelligent agents. This methodology allows a subject matter expert to build an agent in the same way in which the expert would teach a human apprentice. The expert will give the agent specific examples of problems and solutions, explanations of these solutions, or supervise the agent as it solves new problems. During such interactions, the agent learns general rules and concepts, continuously extending and improving its knowledge base. In this paper we present initial results on applying this methodology to build an intelligent adaptive agent for monitoring and repair of the electrical power system of an orbital satellite, stressing the interaction with the expert during apprenticeship learning

Harmonizing BML Approaches: Grammars and Data Models for a BML Standard

Battle Management Language (BML) is being developed as an open standard that unambiguously formalizes and specifies Command and Control information, including orders and reports built upon precise representations of tasks. BML is a language specification, based on doctrine and consistent with Coalition standards. The goal of BML is to enable and improve the interoperability in the C2 area, especially by enabling also the military communication with simulation systems and future robotic forces. Although the need for BML is well documented, a SISO standard has still not been achieved. At present, there are two recommended approaches focusing on different aspects. In order to achieve a SISO standard, the SISO product development group for the development of BML has explored these approaches and presented three possible ways to achieve the standard. On the basis of these recommendations, Bundeswehr’s IT office asked supporters of both BML approaches to discuss possible compromises in order to get the best out of the approaches and to facilitate the definition of the standard. In this paper, a way forward is recommended and explained. In short, this compromise recommends using MBDE’s transactionals as constituents under the C2LG

Harmonizing BML Approaches: Grammars and Data Models for a BML Standard

Battle Management Language (BML) is being developed as an open standard that unambiguously formalizes and specifies Command and Control information, including orders and reports built upon precise representations of tasks. BML is a language specification, based on doctrine and consistent with Coalition standards. The goal of BML is to enable and improve the interoperability in the C2 area, especially by enabling also the military communication with simulation systems and future robotic forces. Although the need for BML is well documented, a SISO standard has still not been achieved. At present, there are two recommended approaches focusing on different aspects. In order to achieve a SISO standard, the SISO product development group for the development of BML has explored these approaches and presented three possible ways to achieve the standard. On the basis of these recommendations, Bundeswehr’s IT office asked supporters of both BML approaches to discuss possible compromises in order to get the best out of the approaches and to facilitate the definition of the standard. In this paper, a way forward is recommended and explained. In short, this compromise recommends using MBDE’s transactionals as constituents under the C2LG

Fluorescence strategies for high-throughput quantification of protein interactions

Advances in high-throughput characterization of protein networks in vivo have resulted in large databases of unexplored protein interactions that occur during normal cell function. Their further characterization requires quantitative experimental strategies that are easy to implement in laboratories without specialized equipment. We have overcome many of the previous limitations to thermodynamic quantification of protein interactions, by developing a series of in-solution fluorescence-based strategies. These methods have high sensitivity, a broad dynamic range, and can be performed in a high-throughput manner. In three case studies we demonstrate how fluorescence (de)quenching and fluorescence resonance energy transfer can be used to quantitatively probe various high-affinity protein–DNA and protein–protein interactions. We applied these methods to describe the preference of linker histone H1 for nucleosomes over DNA, the ionic dependence of the DNA repair enzyme PARP1 in DNA binding, and the interaction between the histone chaperone Nap1 and the histone H2A–H2B heterodimer

M&S Interoperability within the DII COE: Building a Technical Requirements Specification

ABSTRACT: Key to the future interoperability of Simulations wit

An Investigation of Machine Learning Techniques for Use in Training Agents for Military Simulations

Abstract – Agents assist users with performing tasks in computer-based applications. The current practice of building an agent involves a developer programming it for each task it must perform, but agents constructed in this manner are difficult to modify and cannot be trained by a user. Agent-Disciple is a system for training instructable agents through user-agent interaction. In Agent-Disciple a user trains an instructable agent through the interface of the user’s application by providing specific examples of tasks and their solutions, explanations of these solutions and supervises the agent as it performs new tasks. We report here on our work that uses Agent-Disciple to provide a learning agent that can command simulated military forces. Military simulations currently have many limitations in modeling human behavior. While it is relatively straightforward to build models of doctrine, it is difficult to have agents utilize this doctrine in varying contexts. There are too many factors to consider when building deterministic models of behavior, even in well-defined situations. We applied Agent-Disciple to circumvent this problem by using heuristic learning methods. A case study is presented in developing an instructable Company Commander Agent for the Modular Semi-Automated Forces (ModSAF) simulation – a state-of-the-art, real-time, distributed interactive military simulation currently utilized in large-scale training exercises. A ModSAF user can train the Company Commander Agent interactively, using the ModSAF interface, to perform various military missions using the Captain system based on Agent-Disciple. A training session with the agent illustrates the different types of learning interactions available in Agent-Disciple. I