Scientific Definition
Approach motivation — pursuit of rewards and goals.
Plain-English Definition
Approach motivation — pursuit of rewards and goals.
Feynman Explanation
The brain's 'go' system.
Core Principle
Approach motivation — pursuit of rewards and goals.
Mechanisms
Pending editorial review.
Approach motivation — pursuit of rewards and goals.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Sales, founder, and creative roles often select for BAS.
Inputs (Triggers)
Pending editorial review.
Outputs (Behaviors)
Pending editorial review.
Behavioral Signature
The brain's 'go' system.
Examples
- High-BAS individuals show stronger reward-seeking and risk tolerance.
- Sales, founder, and creative roles often select for BAS.
Pending editorial review.
Famous Experiments
Pending editorial review.
Design Principles
- Pair high-BAS individuals with structures that channel approach into productive risk.
Measurement Approaches
Pending editorial review.
Evidence
Pending editorial review.
Pending editorial review.
The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Pair high-BAS individuals with structures that channel approach into productive risk.
Pending editorial review.
Pending editorial review.
Interactive Mini Network
Click any neighbor to re-center the graph and follow the threads of connection.
Knowledge Graph Neighbors
Auto-linked to the rest of the Human Behavior Taxonomy by family, domain, dimension, and shared keywords.
Avoidance motivation — sensitivity to punishment, uncertainty, and threat.
A system with many interacting parts that learn and adapt.
The brain's overnight cleaning system; clears metabolic waste during sleep.
Systems that gain from disorder.
Map reinforcing (R) and balancing (B) feedback loops between variables to see system behavior.
Many interacting parts producing emergent behavior nobody designed.
Single-loop fixes the action. Double-loop questions the goal or model that produced it.
System 1 is fast, automatic, intuitive; System 2 is slow, effortful, deliberate.
Interdependent network of actors evolving together.
The whole has properties that the individual parts do not.
Systems maintain stability by self-regulating around a setpoint.
Subjects often converge to neoclassical predictions only after many rounds of feedback — not on the first try.