scholarly journals Adversarial Argument, Belief Change, and Vulnerability

Topoi ◽  
2021 ◽  
Author(s):  
Moira Howes ◽  
Catherine Hundleby
Keyword(s):  
2021 ◽  
Author(s):  
Antti Gronow ◽  
Maria Brockhaus ◽  
Monica Di Gregorio ◽  
Aasa Karimo ◽  
Tuomas Ylä-Anttila

AbstractPolicy learning can alter the perceptions of both the seriousness and the causes of a policy problem, thus also altering the perceived need to do something about the problem. This then allows for the informed weighing of different policy options. Taking a social network perspective, we argue that the role of social influence as a driver of policy learning has been overlooked in the literature. Network research has shown that normatively laden belief change is likely to occur through complex contagion—a process in which an actor receives social reinforcement from more than one contact in its social network. We test the applicability of this idea to policy learning using node-level network regression models on a unique longitudinal policy network survey dataset concerning the Reducing Deforestation and Forest Degradation (REDD+) initiative in Brazil, Indonesia, and Vietnam. We find that network connections explain policy learning in Indonesia and Vietnam, where the policy subsystems are collaborative, but not in Brazil, where the level of conflict is higher and the subsystem is more established. The results suggest that policy learning is more likely to result from social influence and complex contagion in collaborative than in conflictual settings.


2018 ◽  
Vol 19 (2) ◽  
pp. 1-42
Author(s):  
Sebastian Binnewies ◽  
Zhiqiang Zhuang ◽  
Kewen Wang ◽  
Bela Stantic
Keyword(s):  

Author(s):  
JOHN BELL ◽  
ZHISHENG HUANG

In this paper we present a formal common sense theory of the adoption of perception-based beliefs. We begin with a logical analysis of perception and then consider when perception should lead to belief change. Our theory is intended to apply to perception in humans and to perception in artificial agents at the level of the symbolic interface between a vision system and a belief system. In order to provide a context for our work we relate it to the emerging field of cognitive robotics, give an abstract architecture for an agent which is both embodied and capable of reasoning, and relate this to the concrete architectures of two vision-based surveillance systems.


2021 ◽  
pp. 002200272199554
Author(s):  
Allan Dafoe ◽  
Remco Zwetsloot ◽  
Matthew Cebul

Reputations for resolve are said to be one of the few things worth fighting for, yet they remain inadequately understood. Discussions of reputation focus almost exclusively on first-order belief change— A stands firm, B updates its beliefs about A’s resolve. Such first-order reputational effects are important, but they are not the whole story. Higher-order beliefs—what A believes about B’s beliefs, and so on—matter a great deal as well. When A comes to believe that B is more resolved, this may decrease A’s resolve, and this in turn may increase B’s resolve, and so on. In other words, resolve is interdependent. We offer a framework for estimating higher-order effects, and find evidence of such reasoning in a survey experiment on quasi-elites. Our findings indicate both that states and leaders can develop potent reputations for resolve, and that higher-order beliefs are often responsible for a large proportion of these effects (40 percent to 70 percent in our experimental setting). We conclude by complementing the survey with qualitative evidence and laying the groundwork for future research.


Author(s):  
EMILIANO LORINI

Abstarct We present a general logical framework for reasoning about agents’ cognitive attitudes of both epistemic type and motivational type. We show that it allows us to express a variety of relevant concepts for qualitative decision theory including the concepts of knowledge, belief, strong belief, conditional belief, desire, conditional desire, strong desire, and preference. We also present two extensions of the logic, one by the notion of choice and the other by dynamic operators for belief change and desire change, and we apply the former to the analysis of single-stage games under incomplete information. We provide sound and complete axiomatizations for the basic logic and for its two extensions.


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