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Peter Bro Miltersen

Publications and source records attributed to Peter Bro Miltersen.

At least 19 recordsLinked to original sources

Existence and computation of monomial families of near-optimal strategies for recursive games

In a finite recursive game in the sense of Everett, both players have stationary epsilon-optimal strategies for every epsilon>0. Frederiksen and Miltersen strengthened this result by showing that the strategies for all sufficiently small epsilon can be encoded by finitely many monomials: at every state, all but possibly one of the action probabilities are constants times integer powers of epsilon. The resulting finite symbolic object specifies a strategy for every sufficiently small accuracy. Their proof uses semialgebraic selection and Puiseux series. We give an alternative elementary proof of this regularity theorem for recursive games. We start with stationary strategies that guarantee vectors approaching the value through Everett's one-sided region. After fixing their support, we express, for each pure stationary reply, all absorption probabilities as quotients of directed-forest polynomials with nonnegative coefficients and a common positive denominator. Each payoff is a fixed signed linear combination of these quotients. We then compress the asymptotic orders of the finitely many forest monomials into one integer weight vector. This proof uses neither semialgebraic selection nor Puiseux series. Furthermore, for rational games with a fixed number N of active states, we present a deterministic polynomial-time algorithm that computes a monomial family exactly. It returns all algebraic coefficients in one ordered real univariate representation. The representation length and running time are at most L^{(N+1)^{O(N)}}, where L is the input length.

cs.GT

Safe Quotes for Retroactive Liquidity Pools

Automated market makers exchange assets through liquidity pools whose quoted prices depend on their reserves, with constant product pools being the most common. When such pools reside on different blockchains or shards, a sequence of swaps cannot in general be executed atomically. Aanes et al. introduced lock-swaps and retroactive constant product liquidity pools to provide price guarantees for such a setting. A retroactive pool implicitly maintains a virtual pool for each possible execute/cancel resolution of its active locks. In the presence of active locks, serving a new swap request requires computing a safe quote; a quote with an output that does not exceed the minimum possible output, taken over all virtual pools. The quote being safe is a hard constraint ensuring the integrity of the pool. A soft constraint is to make the quote as close to the minimum possible output as possible. Aanes et al. gave a simple and efficient algorithm for computing the exact minimum when unresolved provides and reclaims of liquidity do not coexist, showed by an explicit example that the algorithm fails in general, and left the computational complexity of the general case open. In this paper, we show that unless P is equal to NP, there is no polynomial time algorithm that computes in the general case a safe quote with any fixed multiplicative approximation ratio (e.g., 50%) relative to the exact minimum. This seems like a severe obstacle for deployment of the lock-swap functionality. However, we also present two simple and practical algorithms for computing safe quotes that have input-dependent approximation ratios that are likely to be satisfactory in practice, thus circumventing that obstacle.

cs.DC

Automated Market Makers for Cross-chain DeFi and Sharded Blockchains

We consider Uniswap-like automated market makers, and, specifically, constant product liquidity pools, operating on blockchains. An important feature of Uniswap is the ability for a trader to carry out a sequence of asset swaps atomically, without other traders changing the prices along the way. This atomic-execution feature is not immediately available in cross-chain or sharded blockchain settings, where different liquidity pools are distributed across different chains or shards. Our contribution is a description and suggested implementation of a new functionality that might be added to individual liquidity pools, the {\em lock-swap}. The lock-swap enables a trader to get a guarantee for the price associated with a swap but only decide later whether or not to carry out the swap. Applied across several liquidity pools, it guarantees the trader assured prices for all swaps in a swap sequence and lets these prices inform the trader's decision about whether or not to carry out the sequence, thus essentially giving the trader the same benefits an atomic execution of the sequence would have provided him. However, in contrast to an atomic execution, our functionality does not prevent other traders from doing swaps during the time where the sequence is planned and possibly carried out. Nor does it prevent liquidity providers from adding or removing liquidity to and from the liquidity pool in that time period.

cs.DC

Walrasian Pricing in Multi-unit Auctions

Multi-unit auctions are a paradigmatic model, where a seller brings multiple units of a good, while several buyers bring monetary endowments. It is well known that Walrasian equilibria do not always exist in this model, however compelling relaxations such as (Walrasian) envy-free pricing do. In this paper we design an optimal envy-free mechanism for multi-unit auctions with budgets. When the market is even mildly competitive, the approximation ratios of this mechanism are small constants for both the revenue and welfare objectives, and in fact for welfare the approximation converges to 1 as the market becomes fully competitive. We also give an impossibility theorem, showing that truthfulness requires discarding resources and, in particular, is incompatible with (Pareto) efficiency.

cs.GT

Computation of Stackelberg Equilibria of Finite Sequential Games

The Stackelberg equilibrium solution concept describes optimal strategies to commit to: Player 1 (termed the leader) publicly commits to a strategy and Player 2 (termed the follower) plays a best response to this strategy (ties are broken in favor of the leader). We study Stackelberg equilibria in finite sequential games (or extensive-form games) and provide new exact algorithms, approximate algorithms, and hardness results for several classes of these sequential games.

cs.GT

Characterization and Computation of Equilibria for Indivisible Goods

We consider the problem of allocating indivisible goods in a way that is fair, using one of the leading market mechanisms in economics: the competitive equilibrium from equal incomes. Focusing on two major classes of valuations, namely perfect substitutes and perfect complements, we establish the computational properties of algorithms operating in this framework. For the class of valuations with perfect complements, our algorithm yields a surprisingly succinct characterization of instances that admit a competitive equilibrium from equal incomes.

cs.GT

Truthful approximations to range voting

We consider the fundamental mechanism design problem of approximate social welfare maximization under general cardinal preferences on a finite number of alternatives and without money. The well-known range voting scheme can be thought of as a non-truthful mechanism for exact social welfare maximization in this setting. With m being the number of alternatives, we exhibit a randomized truthful-in-expectation ordinal mechanism implementing an outcome whose expected social welfare is at least an Omega(m^{-3/4}) fraction of the social welfare of the socially optimal alternative. On the other hand, we show that for sufficiently many agents and any truthful-in-expectation ordinal mechanism, there is a valuation profile where the mechanism achieves at most an O(m^{-{2/3}) fraction of the optimal social welfare in expectation. We get tighter bounds for the natural special case of m = 3, and in that case furthermore obtain separation results concerning the approximation ratios achievable by natural restricted classes of truthful-in-expectation mechanisms. In particular, we show that for m = 3 and a sufficiently large number of agents, the best mechanism that is ordinal as well as mixed-unilateral has an approximation ratio between 0.610 and 0.611, the best ordinal mechanism has an approximation ratio between 0.616 and 0.641, while the best mixed-unilateral mechanism has an approximation ratio bigger than 0.660. In particular, the best mixed-unilateral non-ordinal (i.e., cardinal) mechanism strictly outperforms all ordinal ones, even the non-mixed-unilateral ordinal ones.

cs.GT

The complexity of approximating a trembling hand perfect equilibrium of a multi-player game in strategic form

We consider the task of computing an approximation of a trembling hand perfect equilibrium for an n-player game in strategic form, n >= 3. We show that this task is complete for the complexity class FIXP_a. In particular, the task is polynomial time equivalent to the task of computing an approximation of a Nash equilibrium in strategic form games with three (or more) players.

cs.GT

A Faster Algorithm for Solving One-Clock Priced Timed Games

One-clock priced timed games is a class of two-player, zero-sum, continuous-time games that was defined and thoroughly studied in previous works. We show that one-clock priced timed games can be solved in time m 12^n n^(O(1)), where n is the number of states and m is the number of actions. The best previously known time bound for solving one-clock priced timed games was 2^(O(n^2+m)), due to Rutkowski. For our improvement, we introduce and study a new algorithm for solving one-clock priced timed games, based on the sweep-line technique from computational geometry and the strategy iteration paradigm from the algorithmic theory of Markov decision processes. As a corollary, we also improve the analysis of previous algorithms due to Bouyer, Cassez, Fleury, and Larsen; and Alur, Bernadsky, and Madhusudan.

cs.GT

Equilibria of Chinese Auctions

Chinese auctions are a combination between a raffle and an auction and are held in practice at charity events or festivals. In a Chinese auction, multiple players compete for several items by buying tickets, which can be used to win the items. In front of each item there is a basket, and the players can bid by placing tickets in the basket(s) corresponding to the item(s) they are trying to win. After all the players have placed their tickets, a ticket is drawn at random from each basket and the item is given to the owner of the winning ticket. While a player is never guaranteed to win an item, they can improve their chances of getting it by increasing the number of tickets for that item. In this paper we investigate the existence of pure Nash equilibria in both the continuous and discrete settings. When the players have continuous budgets, we show that a pure Nash equilibrium may not exist for asymmetric games when some valuations are zero. In that case we prove that the auctioneer can stabilize the game by placing his own ticket in each basket. On the other hand, when all the valuations are strictly positive, a pure Nash equilibrium is guaranteed to exist, and the equilibrium strategies are symmetric when both valuations and budgets are symmetric. We also study Chinese auctions with discrete budgets, for which we give both existence results and counterexamples. While the literature on rent-seeking contests traditionally focuses on continuous costly tickets, the discrete variant is very natural and more closely models the version of the auction held in practice.

cs.GT

Solving simple stochastic games with few coin toss positions

Gimbert and Horn gave an algorithm for solving simple stochastic games with running time O(r! n) where n is the number of positions of the simple stochastic game and r is the number of its coin toss positions. Chatterjee et al. pointed out that a variant of strategy iteration can be implemented to solve this problem in time 4^r r^{O(1)} n^{O(1)}. In this paper, we show that an algorithm combining value iteration with retrograde analysis achieves a time bound of O(r 2^r (r log r + n)), thus improving both time bounds. While the algorithm is simple, the analysis leading to this time bound is involved, using techniques of extremal combinatorics to identify worst case instances for the algorithm.

cs.GT

The complexity of solving reachability games using value and strategy iteration

Two standard algorithms for approximately solving two-player zero-sum concurrent reachability games are value iteration and strategy iteration. We prove upper and lower bounds of 2^(m^(Theta(N))) on the worst case number of iterations needed by both of these algorithms for providing non-trivial approximations to the value of a game with N non-terminal positions and m actions for each player in each position. In particular, both algorithms have doubly-exponential complexity. Even when the game given as input has only one non-terminal position, we prove an exponential lower bound on the worst case number of iterations needed to provide non-trivial approximations.

cs.GT

Exact Algorithms for Solving Stochastic Games

Shapley's discounted stochastic games, Everett's recursive games and Gillette's undiscounted stochastic games are classical models of game theory describing two-player zero-sum games of potentially infinite duration. We describe algorithms for exactly solving these games.

cs.GT

Send Mixed Signals -- Earn More, Work Less

Emek et al. presented a model of probabilistic single-item second price auctions where an auctioneer who is informed about the type of an item for sale, broadcasts a signal about this type to uninformed bidders. They proved that finding the optimal (for the purpose of generating revenue) {\em pure} signaling scheme is strongly NP-hard. In contrast, we prove that finding the optimal {\em mixed} signaling scheme can be done in polynomial time using linear programming. For the proof, we show that the problem is strongly related to a problem of optimally bundling divisible goods for auctioning. We also prove that a mixed signaling scheme can in some cases generate twice as much revenue as the best pure signaling scheme and we prove a generally applicable lower bound on the revenue generated by the best mixed signaling scheme.

cs.GT

Strategy iteration is strongly polynomial for 2-player turn-based stochastic games with a constant discount factor

Ye showed recently that the simplex method with Dantzig pivoting rule, as well as Howard's policy iteration algorithm, solve discounted Markov decision processes (MDPs), with a constant discount factor, in strongly polynomial time. More precisely, Ye showed that both algorithms terminate after at most $O(\frac{mn}{1-γ}\log(\frac{n}{1-γ}))$ iterations, where $n$ is the number of states, $m$ is the total number of actions in the MDP, and $0<γ<1$ is the discount factor. We improve Ye's analysis in two respects. First, we improve the bound given by Ye and show that Howard's policy iteration algorithm actually terminates after at most $O(\frac{m}{1-γ}\log(\frac{n}{1-γ}))$ iterations. Second, and more importantly, we show that the same bound applies to the number of iterations performed by the strategy iteration (or strategy improvement) algorithm, a generalization of Howard's policy iteration algorithm used for solving 2-player turn-based stochastic games with discounted zero-sum rewards. This provides the first strongly polynomial algorithm for solving these games, resolving a long standing open problem.

cs.GT

On the computational complexity of solving stochastic mean-payoff games

We consider some well-known families of two-player, zero-sum, perfect information games that can be viewed as special cases of Shapley's stochastic games. We show that the following tasks are polynomial time equivalent: - Solving simple stochastic games. - Solving stochastic mean-payoff games with rewards and probabilities given in unary. - Solving stochastic mean-payoff games with rewards and probabilities given in binary.

cs.GT

Trembling hand perfection is NP-hard

It is NP-hard to decide if a given pure-strategy Nash equilibrium of a given three-player game in strategic form with integer payoffs is trembling hand perfect.

cs.GT

Approximability and parameterized complexity of minmax values

We consider approximating the minmax value of a multi-player game in strategic form. Tightening recent bounds by Borgs et al., we observe that approximating the value with a precision of epsilon log n digits (for any constant epsilon>0 is NP-hard, where n is the size of the game. On the other hand, approximating the value with a precision of c log log n digits (for any constant c >= 1) can be done in quasi-polynomial time. We consider the parameterized complexity of the problem, with the parameter being the number of pure strategies k of the player for which the minmax value is computed. We show that if there are three players, k=2 and there are only two possible rational payoffs, the minmax value is a rational number and can be computed exactly in linear time. In the general case, we show that the value can be approximated with any polynomial number of digits of accuracy in time n^(O(k)). On the other hand, we show that minmax value approximation is W[1]-hard and hence not likely to be fixed parameter tractable. Concretely, we show that if k-CLIQUE requires time n^(Omega(k)) then so does minmax value computation.

cs.GT