AI RESEARCH
The Design and Composition of Structural Causal Decision Processes
arXiv CS.AI
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ArXi:2605.02681v1 Announce Type: cross 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.