21,432 research outputs found
Randomness for Free
We consider two-player zero-sum games on graphs. These games can be
classified on the basis of the information of the players and on the mode of
interaction between them. On the basis of information the classification is as
follows: (a) partial-observation (both players have partial view of the game);
(b) one-sided complete-observation (one player has complete observation); and
(c) complete-observation (both players have complete view of the game). On the
basis of mode of interaction we have the following classification: (a)
concurrent (both players interact simultaneously); and (b) turn-based (both
players interact in turn). The two sources of randomness in these games are
randomness in transition function and randomness in strategies. In general,
randomized strategies are more powerful than deterministic strategies, and
randomness in transitions gives more general classes of games. In this work we
present a complete characterization for the classes of games where randomness
is not helpful in: (a) the transition function probabilistic transition can be
simulated by deterministic transition); and (b) strategies (pure strategies are
as powerful as randomized strategies). As consequence of our characterization
we obtain new undecidability results for these games
Qualitative Analysis of Concurrent Mean-payoff Games
We consider concurrent games played by two-players on a finite-state graph,
where in every round the players simultaneously choose a move, and the current
state along with the joint moves determine the successor state. We study a
fundamental objective, namely, mean-payoff objective, where a reward is
associated to each transition, and the goal of player 1 is to maximize the
long-run average of the rewards, and the objective of player 2 is strictly the
opposite. The path constraint for player 1 could be qualitative, i.e., the
mean-payoff is the maximal reward, or arbitrarily close to it; or quantitative,
i.e., a given threshold between the minimal and maximal reward. We consider the
computation of the almost-sure (resp. positive) winning sets, where player 1
can ensure that the path constraint is satisfied with probability 1 (resp.
positive probability). Our main results for qualitative path constraints are as
follows: (1) we establish qualitative determinacy results that show that for
every state either player 1 has a strategy to ensure almost-sure (resp.
positive) winning against all player-2 strategies, or player 2 has a spoiling
strategy to falsify almost-sure (resp. positive) winning against all player-1
strategies; (2) we present optimal strategy complexity results that precisely
characterize the classes of strategies required for almost-sure and positive
winning for both players; and (3) we present quadratic time algorithms to
compute the almost-sure and the positive winning sets, matching the best known
bound of algorithms for much simpler problems (such as reachability
objectives). For quantitative constraints we show that a polynomial time
solution for the almost-sure or the positive winning set would imply a solution
to a long-standing open problem (the value problem for turn-based deterministic
mean-payoff games) that is not known to be solvable in polynomial time
Observably Deterministic Concurrent Strategies and Intensional Full Abstraction for Parallel-or
International audienceAlthough Plotkin's parallel-or is inherently deterministic, it has a non-deterministic interpretation in games based on (prime) event structures-in which an event has a unique causal history-because they do not directly support disjunctive causality. General event structures can express disjunctive causality and have a more permissive notion of determinism, but do not support hiding. We show that (structures equivalent to) deterministic general event structures do support hiding, and construct a new category of games based on them with a deterministic interpretation of aPCFpor, an affine variant of PCF extended with parallel-or. We then exploit this deterministic interpretation to give a relaxed notion of determinism (observable determinism) on the plain event structures model. Putting this together with our previously introduced concurrent notions of well-bracketing and innocence, we obtain an intensionally fully abstract model of aPCFpor
Thin Games with Symmetry and Concurrent Hyland-Ong Games
We build a cartesian closed category, called Cho, based on event structures.
It allows an interpretation of higher-order stateful concurrent programs that
is refined and precise: on the one hand it is conservative with respect to
standard Hyland-Ong games when interpreting purely functional programs as
innocent strategies, while on the other hand it is much more expressive. The
interpretation of programs constructs compositionally a representation of their
execution that exhibits causal dependencies and remembers the points of
non-deterministic branching.The construction is in two stages. First, we build
a compact closed category Tcg. It is a variant of Rideau and Winskel's category
CG, with the difference that games and strategies in Tcg are equipped with
symmetry to express that certain events are essentially the same. This is
analogous to the underlying category of AJM games enriching simple games with
an equivalence relations on plays. Building on this category, we construct the
cartesian closed category Cho as having as objects the standard arenas of
Hyland-Ong games, with strategies, represented by certain events structures,
playing on games with symmetry obtained as expanded forms of these arenas.To
illustrate and give an operational light on these constructions, we interpret
(a close variant of) Idealized Parallel Algol in Cho
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