Beyond rational imitation: Learning arbitrary means actions from communicative demonstrations

被引:100
|
作者
Kiraly, Ildiko [1 ]
Csibra, Gergely [2 ]
Gergely, Gyorgy [2 ]
机构
[1] Eotvos Lorand Univ, Dept Cognit Psychol, H-1064 Budapest, Hungary
[2] Cent European Univ, Dept Cognit Sci, H-1051 Budapest, Hungary
基金
欧洲研究理事会;
关键词
Rational imitation; Relevance-guided imitation; Teleological stance; Natural pedagogy; Social Learning; Ostensive communication; GOAL ATTRIBUTION; YOUNG-CHILDREN; INFANTS; 12-MONTH-OLD; SELECTION; REASON; AGENCY; CUES;
D O I
10.1016/j.jecp.2012.12.003
中图分类号
B844 [发展心理学(人类心理学)];
学科分类号
040202 ;
摘要
The principle of rationality has been invoked to explain that infants expect agents to perform the most efficient means action to attain a goal. It has also been demonstrated that infants take into account the efficiency of observed actions to achieve a goal outcome when deciding whether to reenact a specific behavior or not. It is puzzling, however, that they also tend to imitate an apparently suboptimal unfamiliar action even when they can bring about the same outcome more efficiently by applying a more rational action alternative available to them. We propose that this apparently paradoxical behavior is explained by infants' interpretation of action demonstrations as communicative manifestations of novel and culturally relevant means actions to be acquired, and we present empirical evidence supporting this proposal. In Experiment 1, we found that 14-month-olds reenacted novel arbitrary means actions only following a communicative demonstration. Experiment 2 showed that infants' inclination to reproduce communicatively manifested novel actions is restricted to behaviors they can construe as goal-directed instrumental acts. The study also provides evidence that infants' reenactment of the demonstrated novel actions reflects epistemic motives rather than purely social motives. We argue that ostensive communication enables infants to represent the teleological structure of novel actions even when the causal relations between means and end are cognitively opaque and apparently violate the efficiency expectation derived from the principle of rationality. This new account of imitative learning of novel means shows how the teleological stance and natural pedagogy two separate cognitive adaptations to interpret instrumental versus communicative actions are integrated as a system for learning socially constituted instrumental knowledge in humans. (C) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码:471 / 486
页数:16
相关论文
共 32 条
  • [1] Adversarial Imitation Learning from Incomplete Demonstrations
    Sun, Mingfei
    Xiaojuan
    [J]. PROCEEDINGS OF THE TWENTY-EIGHTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2019, : 3513 - 3519
  • [2] Robust Imitation Learning from Noisy Demonstrations
    Tangkaratt, Voot
    Charoenphakdee, Nontawat
    Sugiyama, Masashi
    [J]. 24TH INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS (AISTATS), 2021, 130 : 298 - +
  • [3] Programmatic Imitation Learning From Unlabeled and Noisy Demonstrations
    Xin, Jimmy
    Zheng, Linus
    Rahmani, Kia
    Wei, Jiayi
    Holtz, Jarrett
    Dillig, Isil
    Biswas, Joydeep
    [J]. IEEE ROBOTICS AND AUTOMATION LETTERS, 2024, 9 (06): : 4894 - 4901
  • [4] Model predictive optimization for imitation learning from demonstrations
    Hu, Yingbai
    Cui, Mingyang
    Duan, Jianghua
    Liu, Wenjun
    Huang, Dianye
    Knoll, Alois
    Chen, Guang
    [J]. ROBOTICS AND AUTONOMOUS SYSTEMS, 2023, 163
  • [5] Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations
    Zhao, Tianxiang
    Yu, Wenchao
    Wang, Suhang
    Wang, Lu
    Zhang, Xiang
    Chen, Yuncong
    Liu, Yanchi
    Cheng, Wei
    Chen, Haifeng
    [J]. PROCEEDINGS OF THE 29TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, KDD 2023, 2023, : 3513 - 3524
  • [6] InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations
    Li, Yunzhu
    Song, Jiaming
    Ermon, Stefano
    [J]. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 30 (NIPS 2017), 2017, 30
  • [7] Learning Rational Subgoals from Demonstrations and Instructions
    Luo, Zhezheng
    Mao, Jiayuan
    Wu, Jiajun
    Lozano-Perez, Tomas
    Tenenbaum, Joshua B.
    Kaelbling, Leslie Pack
    [J]. THIRTY-SEVENTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 37 NO 10, 2023, : 12068 - 12078
  • [8] Learning Manipulation Actions from a Few Demonstrations
    Abdo, Nichola
    Kretzschmar, Henrik
    Spinello, Luciano
    Stachniss, Cyrill
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2013, : 1268 - 1275
  • [9] Learning Manipulation Actions from Human Demonstrations
    Welschehold, Tim
    Dornhege, Christian
    Burgard, Wolfram
    [J]. 2016 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2016), 2016, : 3772 - 3777
  • [10] Adversarial Imitation Learning from State-only Demonstrations
    Torabi, Faraz
    Warnell, Garrett
    Stone, Peter
    [J]. AAMAS '19: PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS, 2019, : 2229 - 2231