MP-MSG-229-11.pdf — page 4

Orchestrating Manned-Unmanned Missions 
Using AI-Based Tasking System Across Multi-Domain Operations in M&S 
11 - 4 
STO-MP-MSG-229 
 
 
1.1.3 
MUM-Teams Orchestration in MDO 
Table 1: Challenges in MUM-T Considerations. 
Factor 
Human Considerations 
Unmanned Considerations 
Cognition 
Highly variable; affected by experience, 
stress, fatigue, workload, and situational 
awareness. Humans can generalize reasoning 
and adapt to novel scenarios. However, do 
possess many cognitive biases which may 
impact (perception, reasoning, decision, 
attention ...).  
Encoded in algorithms; generally stable across 
situations but may vary among agent types. 
Performance depends on sensor input and 
environment. Machine cognition refers to the 
agent’s ability to process data, reason, and act 
toward a goal. 
Perception 
Limited by human sensory capabilities and 
attention; human concentration and focus 
reducing external noise and distraction, can 
be augmented by tools. It could also be 
impacted by weather. Less training needed to 
identify, 
detect 
and 
assess 
situation. 
Agreement among other humans easier.  
Algorithms process sensor data (vision, lidar, 
radar). Perception quality depends on sensor 
fidelity and algorithm robustness filtering and 
preprocessing. It can extend and process large 
amounts of data but needs large training data to 
be able to detect and classify. More disagreement 
among agents.  
Decision 
Highly varied among humans, some attempt 
to regularize it through doctrine/ rule of 
engagement. Humans tend to be more 
capable of decision making under new 
situations. 
Algorithms follow programmed decision-making 
logic; can be optimized for speed and consistency 
but may struggle in novel, ambiguous situations. 
Psychology 
Human stress, fatigue, and PTSD affect 
performance and team dynamics. 
No psychological impacts; may include failure 
modes from software errors, system degradation, 
or adversarial attacks. 
Leardership 
Humans 
provide 
adaptive 
leadership, 
motivation, and mentoring. Human have 
often the final control. 
Usually 
hard-coded 
(predefined 
command 
hierarchies or behavior trees); advanced systems 
may support emergent coordination rules. Linked 
to a rule-based, doctrine, C2 mission management 
controlled by human. 
Intent  
Humans have clear intentions shaped by 
goals, ethics, and context. 
Given by humans (operator, programmers, C2, 
commanders). 
Must 
be 
inferred 
or 
pre-
programmed; 
intent 
can 
be 
explicitly 
communicated (via command protocols) or 
estimated by the system for planning and 
coordination. 
In MUM-T teams, human and unmanned agents exhibit fundamentally different characteristics that influence 
collaboration and coordination. Human cognition is highly flexible but also subject to variability due to 
stress, workload, experience, and other human factors, which can impact decision-making and situational 
awareness. In contrast, unmanned agents have cognition encoded in algorithms, resulting in consistent 
performance that depends primarily on sensor input and the quality of their reasoning models. Humans rely 
on perception through biological senses, which can be augmented but remain limited, whereas unmanned 
systems utilize algorithmic perception to process data from multiple sensors, enabling faster and more 
precise environmental awareness. Decision-making in humans is adaptive and generalizable, often guided by 
doctrine and experience, while machines follow pre-programmed or learned algorithms that prioritize 
efficiency and consistency. Psychological factors such as fatigue, stress, or PTSD affect humans but have no