Strategies as Concurrent Processes

Castellan, Simon; Hayman, Jonathan; Lasson, Marc; Winskel, Glynn

doi:10.1016/j.entcs.2014.10.006

Cited by 17 publications

(25 citation statements)

References 17 publications

(25 reference statements)

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“…We now construct a category of "uncovered strategies", up to weak bisimulation. Uncovered strategies are very close to the partial strategies of [8], but [8] focused on connections with operational semantics rather than categorical structure.…”

Section: Uncovered Strategies Up To Weak Bisimulationmentioning

confidence: 99%

Non-angelic Concurrent Game Semantics

Castellan

Clairambault

Hayman

et al. 2018

Lecture Notes in Computer Science

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The hiding operation, crucial in the compositional aspect of game semantics, removes computation paths not leading to observable results. Accordingly, games models are usually biased towards angelic non-determinism: diverging branches are forgotten. We present here new categories of games, not suffering from this bias. In our first category, we achieve this by avoiding hiding altogether; instead morphisms are uncovered strategies (with neutral events) up to weak bisimulation. Then, we show that by hiding only certain events dubbed inessential we can consider strategies up to isomorphism, and still get a category-this partial hiding remains sound up to weak bisimulation, so we get a concrete representations of programs (as in standard concurrent games) while avoiding the angelic bias. These techniques are illustrated with an interpretation of affine nondeterministic PCF which is adequate for weak bisimulation; and may, must and fair convergences.

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Section: Uncovered Strategies Up To Weak Bisimulationmentioning

confidence: 99%

Non-angelic Concurrent Game Semantics

Castellan

Clairambault

Hayman

et al. 2018

Lecture Notes in Computer Science

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“…Intuitively it behaves like the copy-cat strategy but where a Player move in the left component may choose to copy from either of the two components on the right. In general the technical definition is involved, even without probability-see [19]. The introduction of probability begins to reveal a limitation within probabilistic strategies as we have defined them, a point we will follow up on in the next section.…”

Section: Extensions: Payoff and Imperfect Informationmentioning

confidence: 99%

“…(In fact, f and g may even be "affine" maps, which don't necessarily preserve empty configurations, provided g∅ ⊑ C f ∅-see [19].) This denotes a deterministic strategy-so a probabilistic strategy with configuration valuation constantly one-provided f reflects −-compatibility and g reflects +-compatibility.…”

Section: Extensions: Payoff and Imperfect Informationmentioning

confidence: 99%

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On Probabilistic Distributed Strategies

Winskel

2015

Lecture Notes in Computer Science

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Abstract. In a distributed game we imagine a team Player engaging a team Opponent in a distributed fashion. No longer can we assume that moves of Player and Opponent alternate. Rather the history of a play more naturally takes the form of a partial order of dependency between occurrences of moves. How are we to define strategies within such a game, and how are we to adjoin probability to such a broad class of strategies? The answer yields a surprisingly rich language of probabilistic distributed strategies and the possibility of programming (optimal) probabilistic strategies. Along the way we shall encounter solutions to: the need to mix probability and nondeterminism; the problem of parallel causes in which members of the same team can race to make the same move, and why this leads us to invent a new model for the semantics of distributed systems.

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“…Firstly, rather than directly representing input moves in the game, we can model them using 'neutral' events in a 'partial strategy' [19]. Composition of partial strategies (such as those for the originator and responder) then has neutral events representing a global session type [20].…”

Section: Conclusion and Related Workmentioning

confidence: 99%

Interaction and Causality in Digital Signature Exchange Protocols

Hayman

2014

Trustworthy Global Computing

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Abstract. Causal reasoning is a powerful tool in analysing security protocols, as seen in the popularity of the strand space model. However, for protocols that branch, more subtle models are called for to capture the ways in which they can interact with a possibly malign environment. We study a model for security protocols encompassing causal reasoning and interaction, developing a semantics for a simple security protocol language based on concurrent games played on event structures. We show how it supports causal reasoning about a protocol for secure digital signature exchange. The semantics paves the way for the application of more sophisticated forms of concurrent game, for example including symmetry and probability, to the analysis of security protocols.

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Strategies as Concurrent Processes

Cited by 17 publications

References 17 publications

Non-angelic Concurrent Game Semantics

Non-angelic Concurrent Game Semantics

On Probabilistic Distributed Strategies

Interaction and Causality in Digital Signature Exchange Protocols

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