Cops vs. Gambler
نویسندگان
چکیده
We consider a variation of cop vs. robber on graph in which the robber is not restricted by the graph edges; instead, he picks a time-independent probability distribution on V (G) and moves according to this fixed distribution. The cop moves from vertex to adjacent vertex with the goal of minimizing expected capture time. Players move simultaneously. We show that when the gambler’s distribution is known, the expected capture time (with best play) on any connected n-vertex graph is exactly n. We also give bounds on the (generally greater) expected capture time when the gambler’s distribution is unknown to the cop.
منابع مشابه
Distributed pursuit algorithms for probabilistic adversaries on connected graphs
A gambler moves between the vertices 1, . . . , n of a graph using the probability distribution p1, . . . , pn. Multiple cops pursue the gambler on the graph, only being able to move between adjacent vertices. We investigate the expected capture time for the gambler against k cops as a function of n and k for three versions of the game: • known gambler: the cops know the gambler’s distribution ...
متن کاملMulti-Armed Bandits, Gittins Index, and its Calculation
Multi-armed bandit is a colorful term that refers to the di lemma faced by a gambler playing in a casino with multiple slot machines (which were colloquially called onearmed bandits). W h a t strategy should a gambler use to pick the machine to play next? It is the one for which the posterior mean of winning is the highest and thereby maximizes current expected reward, or the one for which the ...
متن کاملDiscrete Time Markov Chains 1 Examples
Example 1.1 (Gambler Ruin Problem). A gambler has $100. He bets $1 each game, and wins with probability 1/2. He stops playing he gets broke or wins $1000. Natural questions include: what’s the probability that he gets broke? On average how many games are played? This problem is a special case of the so-called Gambler Ruin problem, which can be modelled using a Markov chain as follows. We will b...
متن کاملOptimal Strategies from Random Walks
We analyze a sequential game between a Gambler and a Casino. The Gambler allocates bets from a limited budget over a fixed menu of gambling events that are offered at equal time intervals, and the Casino chooses a binary loss outcome for each of the events. We derive the optimal min-max strategies for both participants. We then prove that the minimum cumulative loss of the Gambler, assuming opt...
متن کاملKarl Sigman 1 Gambler ’ s Ruin Problem
Let N ≥ 2 be an integer and let 1 ≤ i ≤ N − 1. Consider a gambler who starts with an initial fortune of $i and then on each successive gamble either wins $1 or loses $1 independent of the past with probabilities p and q = 1 − p respectively. Let Xn denote the total fortune after the nth gamble. The gambler’s objective is to reach a total fortune of $N , without first getting ruined (running out...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- CoRR
دوره abs/1308.4715 شماره
صفحات -
تاریخ انتشار 2013