A Meta Lambda Calculus with Cross-Level Computation

被引:0
|
作者
Tobisawa, Kazunori [1 ]
机构
[1] Univ Tokyo, Grad Sch Math Sci, Tokyo 1138654, Japan
关键词
lambda calculus; metavariables; textual substitution; dynamic binding;
D O I
10.1145/2775051.2676976
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
We propose meta lambda calculus lambda* as a basic model of textual substitution via metavariables. The most important feature of the calculus is that every beta-redex can be reduced regardless of whether the beta-redex contains meta-level variables or not. Such a meta lambda calculus has never been achieved before due to difficulty to manage binding structure consistently with alpha-renaming in the presence of meta-level variables. We overcome the difficulty by introducing a new mechanism to deal with substitution and binding structure in a systematic way without the notion of free variables and alpha-renaming. Calculus lambda* enables us to investigate cross-level terms that include a certain type of level mismatch. Cross-level terms have been regarded as meaningless terms and left out of consideration thus far. We find that some cross-level terms behave as quotes and 'eval' command in programming languages. With these terms, we show a procedural language as an application of the calculus, which sheds new light on the notions of stores and recursion via metalevel variables.
引用
收藏
页码:383 / 393
页数:11
相关论文
共 50 条
  • [31] Cross-Level Validation of Topological Quantum Circuits
    Paler, Alexandru
    Devitt, Simon
    Nemoto, Kae
    Polian, Ilia
    REVERSIBLE COMPUTATION, RC 2014, 2014, 8507 : 189 - 200
  • [32] A cross-level study of procedural justice perceptions
    Hon, Alice H. Y.
    Yang, Jixia
    Lu, Lin
    JOURNAL OF MANAGERIAL PSYCHOLOGY, 2011, 26 (7-8) : 700 - 715
  • [33] Face forgery detection with cross-level attention
    Liu, Yaju
    Fei, Jianwei
    Yu, Peipeng
    Yuan, Chengsheng
    Liang, Haopeng
    INTERNATIONAL JOURNAL OF AUTONOMOUS AND ADAPTIVE COMMUNICATIONS SYSTEMS, 2024, 17 (03) : 233 - 246
  • [34] Towards a cross-level theory of neural learning
    Bell, Anthony J.
    BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING, 2007, 954 : 56 - 73
  • [35] Graph similarity learning for cross-level interactions
    Zou, Cuifang
    Lu, Guangquan
    Du, Longqing
    Zeng, Xuxia
    Lin, Shilong
    INFORMATION PROCESSING & MANAGEMENT, 2025, 62 (01)
  • [36] Cross-level sensor network simulation with COOJA
    Osterlind, Fredrik
    Dunkels, Adam
    Eriksson, Joakim
    Finne, Niclas
    Voigt, Thiemo
    31ST IEEE CONFERENCE ON LOCAL COMPUTER NETWORKS, PROCEEDINGS, 2006, : 641 - 648
  • [37] Cross-Level Bias and Variations in Care Reply
    Livingston, Edward H.
    McNutt, Robert A.
    JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2011, 306 (19): : 2097 - 2097
  • [38] ETIOLOGICAL HYPOTHESES IN SCHIZOPHRENIA - CROSS-LEVEL ANALYSIS
    CLEEK, RK
    CLEEK, MG
    JOURNAL OF CLINICAL PSYCHOLOGY, 1984, 40 (06) : 1295 - 1300
  • [39] A cross-level model of organizational commitment antecedents
    Soltani, Morteza
    Hajikarimi, Abbas Ali
    IRANIAN JOURNAL OF MANAGEMENT STUDIES, 2016, 9 (02) : 383 - 405
  • [40] CROSS-LEVEL ANALYSIS - CASE OF SOCIAL INFERENCE
    TEUNE, H
    QUALITY & QUANTITY, 1979, 13 (06) : 527 - 537