Finite Depth Reasoning

Definition ∞ Finite depth reasoning describes a cognitive process where agents consider only a limited number of steps or iterations when strategizing in a game or decision-making scenario. Unlike ideal rational agents who analyze all possible future outcomes, agents employing finite depth reasoning stop their analysis after a certain number of layers, making decisions based on this truncated foresight. This approach accounts for real-world cognitive constraints and computational limitations. It often leads to simpler, yet practically effective, strategies.
Context ∞ In digital asset markets and decentralized protocols, finite depth reasoning is often invoked to explain observed participant behavior that deviates from perfectly rational economic predictions. This concept helps model how traders might react to immediate market signals without fully simulating all long-term consequences. Understanding these reasoning limits is important for designing incentive structures in blockchain governance and for predicting market dynamics where participants operate with incomplete information or processing power.