Army National Guard Leader Development Program

Enhance and support the State's and Territories' capability to develop Army National Guard leader's knowledge, skills, competencies, attributes, and behaviors to produce agile and adaptive leaders at echelon, who are able to operate and succeed in complex and dynamic environments. By Creating and providing leader development resources, opportunities, and content in the experiential and self-development realms of professional development, which deliver broadening experience or increased technical and conceptual competency in order to enable Leader Development across the 54 States and Territories.

Holistic Health & Fitness

H2F is a capabilities-based, task and environment focused, Human Performance Optimization (HPO) program. HQDA EXORD 149-19 directs the Total Army to implement the H2F System. For the Active Component (AC), H2F provides Soldiers direct access to specialized medical and mental health care providers, athletic trainers, and strength coaches at the brigade level. The ARNG model will not mirror the AC model, while still accomplishing the desired end state of improving physical fitness, injury avoidance and recovery, nutritional health, and mental/spiritual resilience.

The ARNG achieves H2F Systems goals of improving Soldier readiness and lethality, optimizing physical/non-physical performance, reducing injury rates, improving rehabilitation after injury, and increasing overall effectiveness through a Directorate enabled and State/Territory led approach which accounts for ARNG unique requirements, opportunities, constraints. The ARNG will accomplish this through a blend of material solutions, subject matter expertise, federal and state resources, and health care professionals.

Workout Video Playlist
Playlist:
Video by Kevin D Schmidt
QuEST (2024-05-24 Joseph Houpt - Mathematical Psychology
Air Force Research Laboratory
May 24, 2024 | 01:00:41
Abstract:

I will give an overview of systems factorial technology (SFT) in the context of the broader motivations of mathematical psychology. A core principle of mathematical psychology is that the measurement of psychological phenomena is theory laden and hence our methodology should be explicitly driven by the theory. SFT is a theory driven methodology focused on measuring how cognitive systems combine distinct sources of information for use. The approach includes formal statements of four logically distinct properties that can distinguish cognitive systems, statistical models to analyze those properties, and guidelines for designing experiments to allow those statistical models to be applied. I will give examples of SFT application to testing interfaces for AI recommender systems and an example of SFT as a meta-theoretical tool applied to testing the ACT-R modeling framework.

Key Moments in the video include:
Define mathematical psychology
Precision in communication
Measurement
Mapping theoretical constructs into numbers
Circular logic
Cognitive modeling
Theory Driven Methodology
Understand how a system combines multiple sources of information
System Factorial Technology (SFT)
Architecture
Stooping Rule
Stochastic Dependence
Workload Capacity
Recap
Workload Capacity Coefficient
UCIP model
First Terminating (OR)
Exhaustive (AND)
Why use C(t)?
Line Length Judgement - Integral vs. Separable Displays
Multisensor Image Fusion
The Survivor Interaction Contrast
The Mean Interaction Contrast
Line Length
Metatheoretical Application of SFT (SFT-GMA)
Global Model Analysis (GMA)
ACT-R
ACT-R Assumptions/Properties
Conclusions
Questions
More

Tags

questAFRLArtificial IntelligenceconsciousnessACT3
More

Up Next

Kabrisky Memorial Lecture 2025
Play Button
01:01:58
Kabrisky Memorial Lecture 2025
Michael Robinson - Topological Features in Large Language Models (and beyond?)
Play Button
01:00:53
Michael Robinson - Topological Features in Large Language Models (and beyond?)
Now Playing
QuEST (2024-05-24 Joseph Houpt - Mathematical Psychology
QuEST (2024-05-24 Joseph Houpt - Mathematical Psychology
Nikolaus Kriegeskorte - Comparing models by their predictions of representational geometries and topologies
Play Button
01:23:26
Nikolaus Kriegeskorte - Comparing models by their predictions of representational geometries and topologies
Lila Davachi - Temporal Integration and Separation of Sequential Events in Memory
Play Button
01:10:36
Lila Davachi - Temporal Integration and Separation of Sequential Events in Memory
Dr. Yubei Chen
Play Button
01:18:31
Dr. Yubei Chen
Anna Schapiro - Learning representations of specifics and generalities over time
Play Button
01:00:12
Anna Schapiro - Learning representations of specifics and generalities over time
Chris Baldassano - Studying memory in the brain with the Method of Loci
Play Button
59:49
Chris Baldassano - Studying memory in the brain with the Method of Loci
Memory Palace
Play Button
59:55
Memory Palace
QuEST Discussion - Memory Athletics Speed Card Methods
Play Button
01:00:41
QuEST Discussion - Memory Athletics Speed Card Methods
Tony & Michael Dottino - USA Memory Athletics Championships
Play Button
57:32
Tony & Michael Dottino - USA Memory Athletics Championships
QuEST - Creation of Flexible Memory
Play Button
01:00:07
QuEST - Creation of Flexible Memory
QuEST - Learning and Memory Conversation
Play Button
58:27
QuEST - Learning and Memory Conversation
Dr. Robert Stickgold - Sleep, Memory, and Dreams: A Unified View
Play Button
01:16:00
Dr. Robert Stickgold - Sleep, Memory, and Dreams: A Unified View
Dr. Chou Hung
Play Button
59:28
Dr. Chou Hung
Dr. Katrina Schleisman - AI and Self
Play Button
56:58
Dr. Katrina Schleisman - AI and Self
Dr. Raj Sharma and Jasper Craig
Play Button
55:05
Dr. Raj Sharma and Jasper Craig
2023 Autonomous Horizons Part 2
Play Button
57:47
2023 Autonomous Horizons Part 2
2023 Autonomous Horizons II, Part 1
Play Button
01:01:02
2023 Autonomous Horizons II, Part 1
Dr. Mica Endsley
Play Button
53:43
Dr. Mica Endsley
Dr. Doug Lenat
Play Button
59:43
Dr. Doug Lenat
Dr. Daniel Dennett
Play Button
01:12:58
Dr. Daniel Dennett
QuEST (2022-02-23) Nelson Dellis - Memory Conversation Part 5
Play Button
59:36
QuEST (2022-02-23) Nelson Dellis - Memory Conversation Part 5
QuEST (2022-02-09) Nelson Dellis - Memory Conversation Part 4
Play Button
01:22:25
QuEST (2022-02-09) Nelson Dellis - Memory Conversation Part 4
Nelson Dellis - Memory Conversation Part 3
Play Button
01:00:47
Nelson Dellis - Memory Conversation Part 3
QuEST (2022-01-05) Nelson Dellis - Memory Conversation Part 2
Play Button
01:09:55
QuEST (2022-01-05) Nelson Dellis - Memory Conversation Part 2
Nelson Dellis - Memory Conversation
Play Button
58:48
Nelson Dellis - Memory Conversation
More Videos

The ARNG will approach H2F as a three phased operation, including defining requirements, experimentation, and implementation. The ARNG H2F implementation strategy is not a universal “one size fits all” approach, States and Territories are afforded the flexibility to experiment through the planning process. FY21 is a planning year for States/Territories to establish those requirements; ARNG requirements will be determined through collaborative, scientific, evidence based research and experimentation. States/Territories conduct market research, small scale pilots, and analysis IOT determine their specific requirements for H2F implementation. Concurrently, ARNG G3 Training Division (TR) will institute a multi-functional working group of industry experts, collegiate human performance centers, and Army professionals to enable collaboration and requirements development. This targeted and individualized approach ensures the collective ARNG requirement possesses relevance, scalability, ease of implementation, effectiveness, and efficiency across the force. The ARNG will report the requirement findings to the Chief of Staff of the Army (CSA) NLT 30 SEP 2021.

 

Application Information

Contact: ngbh2fstaff@army.mil
OIC: LTC William Palmer
NCOIC: MSG David Brooks