Mixed powerdomains for probability and nondeterminism
Klaus Keimel, Gordon D. Plotkin

TL;DR
This paper develops a domain-theoretic framework for mixed powerdomains combining nondeterminism and probability, using convex sets called Kegelspitzen to represent probabilistic algebras and establishing their algebraic and functional properties.
Contribution
It introduces power Kegelspitzen as a new domain-theoretic model for mixed nondeterminism and probability, providing algebraic characterizations and functional representations.
Findings
Power Kegelspitzen are equivalent to probabilistic algebras of Graham and Jones.
Powerdomains are suitable convex sets of subprobability valuations.
The algebraic approach faces difficulties when probabilistic choice is resolved first.
Abstract
We consider mixed powerdomains combining ordinary nondeterminism and probabilistic nondeterminism. We characterise them as free algebras for suitable (in)equation-al theories; we establish functional representation theorems; and we show equivalencies between state transformers and appropriately healthy predicate transformers. The extended nonnegative reals serve as `truth-values'. As usual with powerdomains, everything comes in three flavours: lower, upper, and order-convex. The powerdomains are suitable convex sets of subprobability valuations, corresponding to resolving nondeterministic choice before probabilistic choice. Algebraically this corresponds to the probabilistic choice operator distributing over the nondeterministic choice operator. (An alternative approach to combining the two forms of nondeterminism would be to resolve probabilistic choice first, arriving at a…
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Taxonomy
TopicsBayesian Modeling and Causal Inference · Logic, Reasoning, and Knowledge · Advanced Algebra and Logic
