Glossary

Cognitive continuity is the ability of an AI agent to preserve, retrieve, update and evolve the internal structures that influence its behavior across interactions and over time.

A persistent AI agent is an AI agent whose behavior can be influenced by durable internal state that survives individual interactions and can be retrieved, updated and evolved over time.

Agent memory is the set of mechanisms through which an AI agent retains, retrieves, updates, organizes and uses information from previous states or experiences to influence current and future behavior.

Episodic memory in an AI agent represents specific experiences or events with enough contextual information for those past episodes to be retrieved and used in later reasoning or behavior.

Semantic memory in an AI agent represents generalized knowledge such as facts, concepts, relationships, preferences and learned propositions that can persist beyond individual experiences.

Memory consolidation is the process by which an AI agent transforms accumulated memories into more stable, structured and reusable representations for future cognition.

Memory retrieval is the process by which an AI agent selects stored memories that are relevant to its current context, goals and cognitive process.

Working memory in an AI agent is the limited and dynamically updated information state currently available to active cognition.

Memory forgetting in an AI agent controls how stored information loses retention, accessibility or behavioral influence as its relevance, validity or value changes.

Attention in an AI agent is the process that prioritizes which available observations, memories, goals and internal states receive cognitive processing.

Goal management is the process through which an AI agent represents, prioritizes, monitors and governs desired future states across time.

Planning in an AI agent is the process of constructing and revising structured paths from the current state toward an active goal.

The cognitive process through which an AI agent interprets context, evidence, memory, knowledge, goals, and internal state to derive structured inferences.

Decision making is the cognitive process through which an AI agent evaluates alternatives and selects, defers, or rejects a course of action under goals, evidence, constraints, and uncertainty.

Behavior generation is the process through which an AI agent converts its current cognitive state into candidate behaviors that can be ranked and selected before execution.

Action execution is the governed process through which an AI agent attempts to turn an operational action representation into an actual effect.