The Design and Composition of Structural Causal Decision Processes
We present two new classes of causal models of decision-making agents. Our approach is motivated by the needs of modeling the economics of computing systems. These systems are composed of subsystems and can exhibit endogenous limits on cognitive resources and value discounting. Structural Causal Decision Models (SCDMs) expand on Structural Causal Influence Models. Like SCIMs, they explicitly represent the causal relationships between model variables and the payoffs of agent decisions. Additionally, agent decisions can be constrained by their causal antecedents, and SCDMs can have open root variables for which no probability distribution or structural equation is given. We show that SCDMs ...
| Authors | Sebastian Benthall, Alan Lujan |
|---|---|
| Primary category | cs.CE |
| Published | 4 May 2026 |
| Last updated at source | 4 May 2026 |
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