報(bào)告題目：Reachability in Fuzzy Game Graphs
報(bào)告人: 潘海玉
講座日期：2021-9-17
講座時(shí)間：15:00
報(bào)告地點(diǎn)：騰訊會(huì)議ID：121181901
主辦單位：數(shù)學(xué)與統(tǒng)計(jì)學(xué)院
講座人簡(jiǎn)介： 潘海玉，桂林電子科技大學(xué)副教授，碩士生導(dǎo)師。2009年畢業(yè)于浙江理工大學(xué)，獲得工學(xué)碩士學(xué)位；2012畢業(yè)于華東師范大學(xué)，獲得博士學(xué)位；2013-2017年在陜西師范大學(xué)博士后流動(dòng)站工作。 現(xiàn)任中國(guó)計(jì)算機(jī)學(xué)會(huì)理論計(jì)算機(jī)專委會(huì)執(zhí)行委員、中國(guó)計(jì)算機(jī)學(xué)會(huì)形式化方法專委會(huì)執(zhí)行委員、中國(guó)人工智能學(xué)會(huì)離散智能計(jì)算專委會(huì)委員、中國(guó)邏輯學(xué)會(huì)非經(jīng)典邏輯與計(jì)算專委會(huì)委員和中國(guó)系統(tǒng)工程學(xué)會(huì)模糊數(shù)學(xué)與模糊系統(tǒng)專委會(huì)委員。研究方向?yàn)樾问交椒?、模糊邏輯。?fù)責(zé)主持國(guó)家自然科學(xué)基金面上項(xiàng)目、國(guó)家自然科學(xué)基金地區(qū)項(xiàng)目、中國(guó)博士后基金、廣西自然科學(xué)基金面上項(xiàng)目、廣西可信軟件重點(diǎn)實(shí)驗(yàn)室開放基金。以第一作者身份在IEEE Transactions on Fuzzy Systems，Fuzzy Sets and Systems，International Journal of Approximate Reasoning，Theoretical Computer Science，Fundamenta Informaticae等國(guó)內(nèi)外重要學(xué)術(shù)刊物和國(guó)際會(huì)議發(fā)表論文20余篇，其中中國(guó)計(jì)算機(jī)學(xué)會(huì)推薦國(guó)際學(xué)術(shù)刊物上發(fā)表文章9篇。
講座簡(jiǎn)介：
Two-player turn-based games on graphs (or game graphs for short) and their probabilistic versions have received increasing attention in computer science, especially in the formal verification of reactive systems. However, in the fuzzy setting game graphs are yet to be addressed, although some practical applications, such as modeling fuzzy systems that interact with their environments, appeal to such models. To fill the gap, in this report we propose a fuzzy version of game graphs and focus on the fuzzy game graphs with reachability objectives, which we will refer to as fuzzy reachability games (FRGs). In an FRG, the goal of one player is to maximize her truth value of reaching a given target set, while the other player aims at the opposite. In this framework, we show that FRGs are determined in the sense that for every state, both of the two players have the same value, and there exist optimal memoryless strategies for both players. Moreover, we design algorithms, which achieve polynomial time-complexity in the size of the FRG, to compute the values of all states and the optimal memoryless strategies for the players. In addition, several examples are given to illustrate our motivation and the theoretical development.
