An agent for learning new natural language commands

被引:6
|
作者
Azaria, Amos [1 ,2 ]
Srivastava, Shashank [3 ]
Krishnamurthy, Jayant [4 ]
Labutov, Igor [5 ]
Mitchell, Tom M. [6 ]
机构
[1] Ariel Univ, Dept Comp Sci, Ariel, Israel
[2] Ariel Univ, Data Sci Ctr, Ariel, Israel
[3] Microsoft Res, Redmond, WA USA
[4] Semant Machines, Berkeley, CA USA
[5] LAER AI, New York, NY USA
[6] Carnegie Mellon Univ, Machine Learning Dept, Pittsburgh, PA 15213 USA
关键词
Human-agent interaction; Human-computer interaction; Agents learning from humans; Natural language processing; Machine learning; TASK;
D O I
10.1007/s10458-019-09425-x
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Teaching via natural language is an intuitive way for end users to add functionality to a virtual assistant, enabling them to personalize their assistant with new commands without requiring the intervention of the system developer, who cannot possibly anticipate all of an end user's needs. In this paper we introduce our Learning by Instruction Agent (LIA), the first virtual assistant, for an email domain, that is capable of learning how to perform new commands taught by end users in natural language. LIA grounds the semantics of each command in terms of primitive executable procedures. When a user provides LIA with a command that it does not understand, it prompts the user to explain the command through a sequence of natural language steps. From this input, LIA learns the meaning of the new command and how to generalize the command to novel situations. For example, having been taught how to "forward an email to Alice", it can correctly understand "forward this email to Bob". We show that users that were assigned to interact with LIA completed the task quicker than users assigned to interact with a non-learning agent. These results demonstrate the potential of natural language teaching to improve the capabilities of intelligent personal assistants. We annotated 4759 natural language statements with their associated computer readable execution commands (logical forms) to form a dataset (which we publicize in this paper). We present the performance of several different parser methods on this dataset.
引用
收藏
页数:27
相关论文
共 50 条
  • [31] Talk2Car: Predicting Physical Trajectories for Natural Language Commands
    Deruyttere, Thierry
    Grujicic, Dusan
    Blaschko, Matthew B.
    Moens, Marie-Francine
    IEEE Access, 2022, 10 : 123809 - 123834
  • [32] Talk2Car: Predicting Physical Trajectories for Natural Language Commands
    Deruyttere, Thierry
    Grujicic, Dusan
    Blaschko, Matthew B.
    Moens, Marie-Francine
    IEEE ACCESS, 2022, 10 : 123809 - 123834
  • [33] INTERACTIVE REGRESSION PROGRAM USING FREE FIELD, NATURAL LANGUAGE CONTROL COMMANDS
    LAVE, CA
    BEHAVIORAL SCIENCE, 1973, 18 (02): : 148 - 149
  • [34] A novel modular neuro-fuzzy controller driven by natural language commands
    Pulasinghe, K
    Watanabe, K
    Kiguchi, K
    Izumi, K
    SICE 2001: PROCEEDINGS OF THE 40TH SICE ANNUAL CONFERENCE, INTERNATIONAL SESSION PAPERS, 2001, : 335 - 338
  • [35] COMPUTER COMMANDS IN RESTRICTED NATURAL-LANGUAGE - SOME ASPECTS OF MEMORY AND EXPERIENCE
    SCAPIN, DL
    HUMAN FACTORS, 1981, 23 (03) : 365 - 375
  • [36] Natural language enabled interface agent
    Rubin, SH
    Dai, W
    IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON INTELLIGENT AGENT TECHNOLOGY, PROCEEDINGS, 2004, : 544 - 547
  • [37] Knowledge acquisition from parsing natural language expressions for humanoid robot action commands
    Recupero, Diego Reforgiato
    Spiga, Federico
    INFORMATION PROCESSING & MANAGEMENT, 2020, 57 (06)
  • [38] Learning New Feedforward Motor Commands Based on Feedback Responses
    Maeda, Rodrigo S.
    Gribble, Paul L.
    Pruszynski, J. Andrew
    CURRENT BIOLOGY, 2020, 30 (10) : 1941 - +
  • [39] Preventing Catastrophic Forgetting in Continual Learning of New Natural Language Tasks
    Kar, Sudipta
    Castellucci, Giuseppe
    Filice, Simone
    Malmasi, Shervin
    Rokhlenko, Oleg
    PROCEEDINGS OF THE 28TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, KDD 2022, 2022, : 3137 - 3145
  • [40] A natural language processing based Internet agent
    Yang, MH
    Yang, CC
    Chung, YM
    SMC '97 CONFERENCE PROCEEDINGS - 1997 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5: CONFERENCE THEME: COMPUTATIONAL CYBERNETICS AND SIMULATION, 1997, : 100 - 105