On Assertoric and Directive Signals and the Evolution of Dynamic Meaning

2012 ◽  
Vol 4 (2) ◽  
pp. 232-260 ◽  
Author(s):  
Michael Franke

Basic speech-act distinctions apply quasi-universally across languages, but little attention has been paid so far to formally modelling the evolution of these. Even worse so, standard models of language evolution from evolutionary game theory deliver functionally ambiguous meanings: evolved meanings in Lewisean signalling games seem hybrids between assertions and directives. This has been noted by Lewis (1969) already, but has only recently received renewed attention (Huttegger, 2007; Blume and Board, 2011; Zollman, 2011). Contrary to previous modelling attempts this paper argues that a functional distinction in formal models should be based on criteria that linguistic typology uses to distinguish clause types cross-linguistically. The paper then offers two simple models that delineate assertoric and imperative meanings once by semantic denotation and once by pragmatic effect. The latter requires us to go beyond standard modelling techniques: in order to account for the dynamic meaning element of “giving a directive” we need a mechanism of co-evolving meanings and norms.

2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Zhu Bai ◽  
Mingxia Huang ◽  
Shuai Bian ◽  
Huandong Wu

The emergence of online car-hailing service provides an innovative approach to vehicle booking but has negatively influenced the taxi industry in China. This paper modeled taxi service mode choice based on evolutionary game theory (EGT). The modes included the dispatching and online car-hailing modes. We constructed an EGT framework, including determining the strategies and the payoff matrix. We introduced different behaviors, including taxi company management, driver operation, and passenger choice. This allowed us to model the impact of these behaviors on the evolving process of service mode choice. The results show that adjustments in taxi company, driver, and passenger behaviors impact the evolutionary path and convergence speed of our evolutionary game model. However, it also reveals that, regardless of adjustments, the stable states in the game model remain unchanged. The conclusion provides a basis for studying taxi system operation and management.


Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 215 ◽  
Author(s):  
Yu Yang ◽  
Bichen Che ◽  
Yang Zeng ◽  
Yang Cheng ◽  
Chenyang Li

With the rapid development and widespread applications of Internet of Things (IoT) systems, the corresponding security issues are getting more and more serious. This paper proposes a multistage asymmetric information attack and defense model (MAIAD) for IoT systems. Under the premise of asymmetric information, MAIAD extends the single-stage game model with dynamic and evolutionary game theory. By quantifying the benefits for both the attack and defense, MAIAD can determine the optimal defense strategy for IoT systems. Simulation results show that the model can select the optimal security defense strategy for various IoT systems.


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