Dynamic Programming for One-sided Partially Observable Pursuit-evasion Games

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00315211" target="_blank" >RIV/68407700:21230/17:00315211 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.5220/0006190605030510" target="_blank" >http://dx.doi.org/10.5220/0006190605030510</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0006190605030510" target="_blank" >10.5220/0006190605030510</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Dynamic Programming for One-sided Partially Observable Pursuit-evasion Games

Popis výsledku v původním jazyce

Pursuit-evasion scenarios appear widely in robotics, security domains, and many other real-world situations. We focus on two-player pursuit-evasion games with concurrent moves, infinite horizon, and discounted rewards. We assume that the players have partial observability, however, the evader has an advantage of knowing the current position of pursuer’s units. This setting is particularly interesting for security domains where a robust strategy, maximizing the utility in the worst-case scenario, is often desirable. We provide, to the best of our knowledge, the first algorithm that provably converges to the value of a partially observable pursuitevasion game with infinite horizon. Our algorithm extends well-known value iteration algorithm by exploiting that (1) value functions of our game depend only on the position of the pursuer and the belief he has about the position of the evader, and (2) that these functions are piecewise linear and convex in the belief space.

Název v anglickém jazyce

Dynamic Programming for One-sided Partially Observable Pursuit-evasion Games

Popis výsledku anglicky

Pursuit-evasion scenarios appear widely in robotics, security domains, and many other real-world situations. We focus on two-player pursuit-evasion games with concurrent moves, infinite horizon, and discounted rewards. We assume that the players have partial observability, however, the evader has an advantage of knowing the current position of pursuer’s units. This setting is particularly interesting for security domains where a robust strategy, maximizing the utility in the worst-case scenario, is often desirable. We provide, to the best of our knowledge, the first algorithm that provably converges to the value of a partially observable pursuitevasion game with infinite horizon. Our algorithm extends well-known value iteration algorithm by exploiting that (1) value functions of our game depend only on the position of the pursuer and the belief he has about the position of the evader, and (2) that these functions are piecewise linear and convex in the belief space.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA15-23235S" target="_blank" >GA15-23235S: Abstrakce a extenzivní hry s nedokonalou pamětí</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2

ISBN

978-989-758-220-2

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

503-510

Název nakladatele

SciTePress - Science and Technology Publications

Místo vydání

Porto

Místo konání akce

Porto

Datum konání akce

24. 2. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000413244200052