Utilizing Multiple Agents for Decision Making in a Fighting Game

Author(s):  
Yoshina Takano ◽  
Suguru Ito ◽  
Tomohiro Harada ◽  
Ruck Thawonmas
Author(s):  
Ulrich G. Strunz

AbstractThe aim of this thesis was to create a decision-making domain, in which multiple agents would collectively engage a problem, without being able to communicate with each other. Furthermore, the group decision making was structured such that each agent would always have an influence over the outcome, but could not control the impact of their decisions. Different information conditions simulated information asymmetries, from which potential behavioral changes were to be analyzed.


2020 ◽  
Vol 34 (09) ◽  
pp. 13520-13524
Author(s):  
Ulle Endriss

Many challenging problems of scientific, technological, and societal significance require us to aggregate information supplied by multiple agents into a single piece of information of the same type—the collective information representing the stance of the group as a whole. Examples include expressive forms of voting and democratic decision making (where citizens supply information regarding their preferences), peer evaluation (where participants supply information in the form of assessments of their peers), and crowdsourcing (where volunteers supply information by annotating data). In this position paper, I outline the challenge of modelling, handling, and analysing all of these diverse instances of collective information using a common methodology. Addressing this challenge will facilitate a transfer of knowledge between different application domains, thereby enabling progress in all of them.


2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.


2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.


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