555 research outputs found
Program Equilibria and Discounted Computation Time
Tennenholtz (GEB 2004) developed Program Equilibrium to model play in a finite two-player game where each player can base their strategy on the other player's strategies. Tennenholtz's model allowed each player to produce a "loop-free" computer program that had access to the code for both players. He showed a folk theorem where any mixed-strategy individually rational play could be an equilibrium payo in this model even in a one-shot game. Kalai et al. gave a general folk theorem for correlated play in a more generic commitment model. We develop a new model of program equilibrium using general computational models and discounting the payos based on the computation time used. We give an even more general folk theorem giving correlated-strategy payoffs down to the pure minimax of each player. We also show equilibrium in other games not covered by the earlier work.brokers, applied mechanism design, linear commission fees, optimal indirect mechanisms, internet auctions, auction houses.
Multi-outcome and Multidimensional Market Scoring Rules
Hanson's market scoring rules allow us to design a prediction market that
still gives useful information even if we have an illiquid market with a
limited number of budget-constrained agents. Each agent can "move" the current
price of a market towards their prediction.
While this movement still occurs in multi-outcome or multidimensional markets
we show that no market-scoring rule, under reasonable conditions, always moves
the price directly towards beliefs of the agents. We present a modified version
of a market scoring rule for budget-limited traders, and show that it does have
the property that, from any starting position, optimal trade by a
budget-limited trader will result in the market being moved towards the
trader's true belief. This mechanism also retains several attractive strategic
properties of the market scoring rule
Bounding Rationality by Discounting Time
Consider a game where Alice generates an integer and Bob wins if he can
factor that integer. Traditional game theory tells us that Bob will always win
this game even though in practice Alice will win given our usual assumptions
about the hardness of factoring.
We define a new notion of bounded rationality, where the payoffs of players
are discounted by the computation time they take to produce their actions. We
use this notion to give a direct correspondence between the existence of
equilibria where Alice has a winning strategy and the hardness of factoring.
Namely, under a natural assumption on the discount rates, there is an
equilibriumwhere Alice has a winning strategy iff there is a linear-time
samplable distribution with respect to which Factoring is hard on average.
We also give general results for discounted games over countable action
spaces, including showing that any game with bounded and computable payoffs has
an equilibrium in our model, even if each player is allowed a countable number
of actions. It follows, for example, that the Largest Integer game has an
equilibrium in our model though it has no Nash equilibria or epsilon-Nash
equilibria.Comment: To appear in Proceedings of The First Symposium on Innovations in
Computer Scienc
Bounding Rationality by Discounting Time
Consider a game where Alice generates an integer and Bob wins if he can factor that integer. Traditional game theory tells us that Bob will always win this game even though in practice Alice will win given our usual assumptions about the hardness of factoring. We define a new notion of bounded rationality, where the payoffs of players are discounted by the computation time they take to produce their actions. We use this notion to give a direct correspondence between the existence of equilibria where Alice has a winning strategy and the hardness of factoring. Namely, under a natural assumption on the discount rates, there is an equilibriumwhere Alice has a winning strategy iff there is a linear-time samplable distribution with respect to which Factoring is hard on average. We also give general results for discounted games over countable action spaces, including showing that any game with bounded and computable payoffs has an equilibrium in our model, even if each player is allowed a countable number of actions. It follows, for example, that the Largest Integer game has an equilibrium in our model though it has no Nash equilibria or E-Nash equilibria.Bounded rationality; Discounting; Uniform equilibria; Factoring game
Hardness of approximation for quantum problems
The polynomial hierarchy plays a central role in classical complexity theory.
Here, we define a quantum generalization of the polynomial hierarchy, and
initiate its study. We show that not only are there natural complete problems
for the second level of this quantum hierarchy, but that these problems are in
fact hard to approximate. Using these techniques, we also obtain hardness of
approximation for the class QCMA. Our approach is based on the use of
dispersers, and is inspired by the classical results of Umans regarding
hardness of approximation for the second level of the classical polynomial
hierarchy [Umans, FOCS 1999]. The problems for which we prove hardness of
approximation for include, among others, a quantum version of the Succinct Set
Cover problem, and a variant of the local Hamiltonian problem with hybrid
classical-quantum ground states.Comment: 21 pages, 1 figure, extended abstract appeared in Proceedings of the
39th International Colloquium on Automata, Languages and Programming (ICALP),
pages 387-398, Springer, 201
Derandomizing from Random Strings
In this paper we show that BPP is truth-table reducible to the set of
Kolmogorov random strings R_K. It was previously known that PSPACE, and hence
BPP is Turing-reducible to R_K. The earlier proof relied on the adaptivity of
the Turing-reduction to find a Kolmogorov-random string of polynomial length
using the set R_K as oracle. Our new non-adaptive result relies on a new
fundamental fact about the set R_K, namely each initial segment of the
characteristic sequence of R_K is not compressible by recursive means. As a
partial converse to our claim we show that strings of high
Kolmogorov-complexity when used as advice are not much more useful than
randomly chosen strings
Quantum Property Testing
A language L has a property tester if there exists a probabilistic algorithm
that given an input x only asks a small number of bits of x and distinguishes
the cases as to whether x is in L and x has large Hamming distance from all y
in L. We define a similar notion of quantum property testing and show that
there exist languages with quantum property testers but no good classical
testers. We also show there exist languages which require a large number of
queries even for quantumly testing
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