Radha Jagadeesan

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An intensional model for the programming language PCF is described, in which the types of PCF are interpreted by games, and the terms by certain “history-free” strategies. This model is shown to capture definability in PCF. More precisely, every compact strategy in the model is definable in a certain simple extension of PCF. We then introduce an intrinsic(More)
We present a game semantics for Linear Logic, in which formulas denote games and proofs denote winning strategies. We show that our semantics yields a categorical model of Linear Logic and prove full completeness for Multiplicative Linear Logic with the MIX rule: every winning strategy is the denotation of a unique cut-free proof net. A key role is played(More)
We develop a model for timed, reactive computation by extending the asynchronous, untimed concurrent constraint programming model in a simple and uniform way. In the spirit of process algebras, we develop some combinators expressible in this model, and reconcile their operational, logical and denotational character. We show how programs may be compiled into(More)
We present Kripke modal transition systems (Kripke MTSs), a generalization of modal transition systems [27,26], as a foundation for three-valued program analysis. The semantics of Kripke MTSs are presented by means of a mixed power domain of states; soundness and consistency are proved. Two major applications, model checking partial state spaces and(More)
The notion of process equivalence of probabilistic processes is sensitive to the exact probabilities of transitions. Thus, a slight change in the transition probabilities will result in two equivalent processes being deemed no longer equivalent. This instability is due to the quantitative nature of probabilistic processes. In a situation where the process(More)
We observe that equivalence is not a robust concept in the presence of numerical information such as probabilities in the model. We develop a metric analogue of weak bisimulation in the spirit of our earlier work on metric analogues for strong bisimulation. We give a fixed point characterization of the metric. This makes available coinductive reasoning(More)
Partial Labeled Markov Chains are simultaneously generalizations of process algebra and of traditional Markov chains. They provide a foundation for interacting discrete probabilistic systems, the interaction being synchronization on labels as in process algebra. Existing notions of process equivalence are too sensitive to the exact probabilities of various(More)