Cognition · Software component

Strategic Agent

Software componentCognitionCognition & Memoryarc:StrategicAgent

A self-interested agent that selects strategies by reasoning about or learning from competitors' actions in a non-cooperative environment.

Responsibility. Chooses actions that maximise its own payoff against competing agents.

Also known as: Competitive agent, Game-theoretic agent

Direct neighbourhood (hover for relationship types)

Relationships

receives delegation from dependency

Auction Task Allocator Ch1.3

sends data to dynamic

Auction Task Allocator Ch1.3

is monitored by assurance

Collusion Monitor Ch1.3

Design guidance

SHOULD NOT treat Nash equilibrium as collectively optimal; equilibria may be inefficient or multiple.
SHOULD expect non-stationarity when competitors learn simultaneously; convergence guarantees vanish.
SHOULD be hardened against adversarial observation, action and environment attacks, which transfer across agent architectures.

Classification

Patterns: Nash equilibriumDominant strategyIterated elimination of dominated strategiesMulti-agent reinforcement learningOpponent modelling
Quality attributes: Flexibility (ISO/IEC 25010)
Risks mitigated: Exploitation by competitors

Sources

Ch1.3: T. Nguyen, "Multi-Agent Systems," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 1.3. ISBN: 9798244538229.