Research of Decision-Making in the Multi-Agent System Based on Interactive Influence Diagrams

2011 ◽  
Vol 467-469 ◽  
pp. 1947-1952
Author(s):  
Bo Li ◽  
Jian Luo ◽  
Jin Fa Zhuang
Keyword(s):  
Decision Making ◽  
Mental Models ◽  
Mental Model ◽  
High Accuracy ◽  
Influence Diagrams ◽  
Multi Agent System ◽  
Empirical Results ◽  
Model Spaces ◽  
Multi Agent ◽  
Sufficient Space

Interactive influence diagrams(I-IDs) offer a transparent and representation for the decision-making in multiagent settings. In I-IDs, for the sake of predicting the behavior of other agent accurately, the modeling agent starts from an initial set of possible models for another agent and then maintains belief about which of those models applies. This initial set of models in the model node is typically a fully specification of possible agent types. Although such a rich space gives the modeling agent high accuracy in its beliefs, it will also incur high cost in maintaining those beliefs. In this paper, we demonstrate that we can choose a minimal, but sufficient, space of mental models by combining models that action or utility equivalence. We illustrate our framework using the two-tiger game and provide empirical results by showing the minimal mental model spaces that it generates.

scholarly journals Networks of Influence Diagrams: A Formalism for Representing Agents' Beliefs and Decision-Making Processes

2008 ◽  
Vol 33 ◽  
pp. 109-147 ◽  
Author(s):  
Y. Gal ◽  
A. Pfeffer
Keyword(s):  
Decision Making ◽  
Mental Models ◽  
Mental Model ◽  
Expressive Language ◽  
Optimal Strategies ◽  
Influence Diagrams ◽  
Bayesian Games ◽  
Opponent Modeling ◽  
Decision Making Processes ◽  
Networks Of Influence Diagrams

This paper presents Networks of Influence Diagrams (NID), a compact, natural and highly expressive language for reasoning about agents' beliefs and decision-making processes. NIDs are graphical structures in which agents' mental models are represented as nodes in a network; a mental model for an agent may itself use descriptions of the mental models of other agents. NIDs are demonstrated by examples, showing how they can be used to describe conflicting and cyclic belief structures, and certain forms of bounded rationality. In an opponent modeling domain, NIDs were able to outperform other computational agents whose strategies were not known in advance. NIDs are equivalent in representation to Bayesian games but they are more compact and structured than this formalism. In particular, the equilibrium definition for NIDs makes an explicit distinction between agents' optimal strategies, and how they actually behave in reality.

Defining the Phenomenon of Mental Models for Critical Events

2013 ◽  
Author(s):  
Kanter van Deurzen ◽  
Imre Horváth ◽  
Regine Vroom
Keyword(s):  
Decision Making ◽  
Mental Models ◽  
Mental Model ◽  
Real Life ◽  
Critical Events ◽  
Cognitive Representations ◽  
Related Information ◽  
Strong Relation ◽  
Decision Making Processes ◽  
Definition Of

People use cognitive representations in order to characterize, understand, reason and predict the surrounding world. A class of these representations are called mental models. Designers of informing systems are interested in how mental models influence decision making, especially during critical events. With this knowledge they could optimize the content and amount of information that is needed for a dependable decision making process. New insights are needed about the operation of mental models in the course of critical events, as well as on how informing influences the real life operationalization of mental models. Most of the definitions available in the literature are overly general, and no definition was found that would support the design of informing systems for critical events. Therefore, the objective of our research was to derive a definition of mental models that play a role in critical events. Actually, we systematically constructed a definition from those attributes of mental model descriptions that were found to be relevant to critical events. First we decomposed 125 published descriptions to a set of attributes, and then assessed each attribute to see if they were associated with critical events, or not. In fact, this analysis involved not only the relevance of the attributes to critical events, but also the frequency of occurrence in the surveyed papers. This exploration provided a large number of attributes for a new mental model definition. Based on the top rated attributes, a definition was synthesized which, theoretically, has a strong relation to critical events. Though further validation will be needed, we argue that the derived mental model definition is strong because it establishes relationships with all generic features of critical events and makes the related information contents explicit. Hence the proposed definition can be considered a starting platform for investigations of the influence of informing on decision making processes in critical events.

Quantifying the search space for multi-agent system decision-making organizations

2002 ◽  
Vol 14 (4) ◽  
pp. 265-281 ◽  
Author(s):  
K. SUZANNE BARBER ◽  
MATTHEW MACMAHON ◽  
CHERYL MARTIN
Keyword(s):  
Decision Making ◽  
Search Space ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent

scholarly journals Artificial Intelligence-Virtual Trainer: An educative system based on artificial intelligence and designed to produce varied and consistent training lessons

2016 ◽  
Vol 231 (2) ◽  
pp. 110-124 ◽  
Author(s):  
Julien Henriet
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Ordered Set ◽  
Case Based Reasoning ◽  
Adaptation Process ◽  
Multi Agent System ◽  
Multi Agent ◽  
Different Parts ◽  
Case Based ◽  
Underlying Theme

AI-Virtual Trainer is an educative system using Artificial Intelligence to propose varied lessons to trainers. The agents of this multi-agent system apply case-based reasoning to build solutions by analogy. However, as required by the field, Artificial Intelligence-Virtual Trainer never proposes the same lesson twice, whereas the same objective may be set many times consecutively. The adaptation process of Artificial Intelligence-Virtual Trainer delivers an ordered set of exercises adapted to the objectives and sub-objectives chosen by trainers. This process has been enriched by including the notion of distance between exercises: the proposed tasks are not only appropriate but are hierarchically ordered. With this new version of the system, students are guided towards their objectives via an underlying theme. Finally, the agents responsible for the different parts of lessons collaborate with each other according to a dedicated protocol and decision-making policy since no exercise must appear more than once in the same lesson. The results prove that Artificial Intelligence-Virtual Trainer, however perfectible, meets the requirements of this field.

Case Study: The Wrong Mental Model can Kill You

2007 ◽  
Vol 51 (9) ◽  
pp. 554-558 ◽  
Author(s):  
Kenneth Nemire
Keyword(s):  
Decision Making ◽  
Mental Models ◽  
Mental Model ◽  
External World ◽  
Roller Coaster ◽  
Internal Representations ◽  
Study Participants

Mental models are internal representations of the external world that are thought to influence perception and decision-making. An inappropriate mental model of a “roller coaster” was hypothesized to have caused the injury of one person and the death of another in a roller coaster incident. A study was conducted to learn about existing internal representations of roller coasters. Participants were asked to draw a roller coaster. Despite the existence of several types of roller coasters, 98% of the study participants drew a roller coaster representing the oldest and most prevalent type of coaster. The results of the study are discussed with respect to this injury incident and the importance of educating product users about more appropriate mental models that may help prevent injury or death.

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