Dynamic Network Techniques for Autonomous Planning and Control
Judea Pearl · 2000
Starting with functional description of physical mechanisms we were able to derive the standard probabilistic properties of Bayesian networks and to show: (1) how the effects of unanticipated actions can be predicted from the net-work topology, (2) how qualitative causal judgments can be integrated with statistical data, (3) how actions interact with observations, (4) how counterfactuals sentences can be interpreted and evaluated, (5) how explanations and single-event causation can be defined in a given causal model.