How do we determine what beliefs and conclusions are reasonable when faced with limited information? The philosophical theory of "inference to the best explanation" offers guidance.
This approach to justified reasoning posits that even without definitive proof, we can rationally infer what most likely explains a given phenomenon based on available evidence and using logic to compare competing hypotheses.
For example, say your kitchen floor is wet, but you didn't spill anything. You could imagine possible explanations like the sink is leaking, a housemate spilled something and cleaned it up, or the floor mysteriously became wet on its own. While not conclusive, the leaky sink best explains the wet floor based on past experiences with no competing discernible causes.
Inference to the best explanation evaluates explanatory power, falsifiability, modesty, and does not rely on deductive certainty. It aims for the most plausible account, not an ironclad one.
Applications range from detectives reasoning to the most probable suspect, doctors diagnosing mysterious symptoms, and scientists evaluating theories about reality based on experimental results. Jurors also use this type of inference when weighing evidenced guilt “beyond reasonable doubt.”
Of course, determining the “best” explanation remains subjective. But systematically applying criteria for logical coherence, explanatory scope and power, applicability to new evidence, and others can minimize cognitive biases. We likely can't achieve Cartesian deductive certainty, but we can ascend towards truth through reason's steps.
While rarely foolproof, inference to the best explanation allows gradually modeling reality through our limited perceptions. By stitching together likely causes behind effects, we construct temporary maps awaiting improved theories that more seamlessly unify our momentary views into an elegant, enduring vision.