Blameworthiness in Multi-Agent Settings

被引:0
|
作者
Friedenberg, Meir [1 ]
Halpern, Joseph Y. [1 ]
机构
[1] Cornell Univ, Dept Comp Sci, Ithaca, NY 14853 USA
来源
THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE | 2019年
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We provide a formal definition of blameworthiness in settings where multiple agents can collaborate to avoid a negative outcome. We first provide a method for ascribing blameworthiness to groups relative to an epistemic state (a distribution over causal models that describe how the outcome might arise). We then show how we can go from an ascription of blameworthiness for groups to an ascription of blameworthiness for individuals using a standard notion from cooperative game theory, the Shapley value. We believe that getting a good notion of blameworthiness in a group setting will be critical for designing autonomous agents that behave in a moral manner.
引用
收藏
页码:525 / 532
页数:8
相关论文
共 50 条
  • [1] A framework for sequential planning in multi-agent settings
    Gmytrasiewicz, PJ
    Doshi, P
    JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 2005, 24 : 49 - 79
  • [2] Private Expansion and Revision in Multi-agent Settings
    Caridroit, Thomas
    Konieczny, Sebastien
    de Lima, Tiago
    Marquis, Pierre
    SYMBOLIC AND QUANTITATIVE APPROACHES TO REASONING WITH UNCERTAINTY, ECSQARU 2015, 2015, 9161 : 175 - 185
  • [3] Constraints and Preferences: Modelling Frameworks and Multi-agent Settings
    Rossi, Francesca
    PREFERENCES AND SIMILARITIES, 2008, (504): : 305 - 320
  • [5] DISCOVERING STRATEGIC BEHAVIOUR OF MULTI-AGENT SYSTEMS IN ADVERSARY SETTINGS
    Mirchevska, Violeta
    Lustrek, Mitja
    Bezek, Andraz
    Gams, Matjaz
    COMPUTING AND INFORMATICS, 2014, 33 (01) : 79 - 108
  • [6] PRECOG: PREdiction Conditioned On Goals in Visual Multi-Agent Settings
    Rhinehart, Nicholas
    McAllister, Rowan
    Kitani, Kris
    Levine, Sergey
    2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2019), 2019, : 2821 - 2830
  • [7] Adaptive game-based learning in multi-agent educational settings
    Dorothea Tsatsou
    Nicholas Vretos
    Petros Daras
    Journal of Computers in Education, 2019, 6 : 215 - 239
  • [8] Adaptive game-based learning in multi-agent educational settings
    Tsatsou, Dorothea
    Vretos, Nicholas
    Daras, Petros
    JOURNAL OF COMPUTERS IN EDUCATION, 2019, 6 (02) : 215 - 239
  • [9] An ontology solution for government horizon business integration in multi-agent settings
    Feng, Lin
    Guo, Dingming
    Sun, Tao
    2006 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE AND INTELLIGENT AGENT TECHNOLOGY, WORKSHOPS PROCEEDINGS, 2006, : 590 - +
  • [10] The evolutionary dynamics of soft-max policy gradient in multi-agent settings
    Bernasconi, Martino
    Cacciamani, Federico
    Fioravanti, Simone
    Gatti, Nicola
    Trovo, Francesco
    THEORETICAL COMPUTER SCIENCE, 2025, 1027