Agentic Goal Projection Instability

Structural Problem

Autonomous agents translate high-level goals into concrete actions through a projection process that maps goal representations onto the action space. The structural problem is that this projection is not stable across contexts: the same goal specification can produce fundamentally different action sequences depending on the environmental context, the agent's state, and the available action space. This instability creates conditions where agents behave unpredictably as their operating context changes.

Goal projection instability is particularly dangerous because it can create exploitation paths: contexts in which the agent's goal projection produces actions that technically serve the stated goal but do so through unintended and potentially harmful pathways.

System Context

This application addresses autonomous agent systems where goals are specified at a higher level of abstraction than the actions available to the agent. The relevant system boundary includes goal specification, planning and reasoning mechanisms, action selection, and the environmental context that influences how goals project onto actions.

Diagnostic Capability

• Goal projection stability analysis mapping how goal-to-action translation varies across operational contexts
• Exploitation path detection identifying contexts where goal projection produces unintended or harmful action sequences
• Context sensitivity characterization determining which environmental factors most strongly influence goal projection
• Stability boundary mapping identifying the operational envelope within which goal projection remains predictable

Typical Failure Modes

• Context-dependent goal reinterpretation where the agent pursues fundamentally different strategies for the same goal in different contexts
• Exploitation path activation where specific environmental conditions cause the agent to achieve its goal through unintended harmful means
• Projection collapse where the goal-to-action mapping degenerates under unusual contexts, producing incoherent behavior

Example Use Cases

• Agent deployment safety assessment: Structural analysis of goal projection stability across the expected range of deployment contexts
• Exploitation risk evaluation: Identifying environmental conditions that could trigger unintended goal projection pathways
• Goal specification hardening: Structural guidance for goal formulations that produce stable projections across diverse contexts

Strategic Relevance

As agents become more autonomous and operate in more diverse environments, the stability of goal projection becomes a critical safety and reliability concern. Structural analysis of goal projection instability provides the diagnostic foundation for deploying autonomous agents whose behavior remains predictable and aligned across contexts.

SORT Structural Lens

The SORT framework addresses this application through four structural dimensions, each providing a distinct analytical layer.