Ethical Decision-Making Framework Based on Incremental ILP Considering Conflicts
作者机构:Guangxi Key Laboratory of Trusted SoftwareGuilin University of Electronic TechnologyGuilin541004China
出 版 物:《Computers, Materials & Continua》 (计算机、材料和连续体(英文))
年 卷 期:2024年第78卷第3期
页 面:3619-3643页
核心收录:
学科分类:12[管理学] 1202[管理学-工商管理] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0702[理学-物理学] 0801[工学-力学(可授工学、理学学位)] 0812[工学-计算机科学与技术(可授工学、理学学位)] 081202[工学-计算机软件与理论]
基 金:This work was funded by the National Natural Science Foundation of China Nos.U22A2099,61966009,62006057 the Graduate Innovation Program No.YCSW2022286
主 题:Ethical decision-making inductive logic programming incremental learning conflicts
摘 要:Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical *** the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of ***,an ethical decision-making framework is constructed by rule-based or statistical *** this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical *** the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP *** framework consists of two processes:the learning process and the deduction *** first process records bottom clauses with their score functions and learns rules guided by the entailment and the score *** second process obtains an ethical decision based on the *** an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical ***,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict *** results of comparisons show that our proposed system can generate better-quality rules than most other systems.