A New Approach to Social Behavior Simulation: The Mask Model

2005

Borrowing ideas from the notion of social construction of self, this paper puts forth the idea of synthetic social construction -multiagent systems in which agents socially construct each others' roles and behaviors via their interactions with one another. An example implementation of synthetic social construction is presented demonstrating one use of this method to facilitate behavior akin to social learning. Synthetic social construction represents a novel approach to adaptive behavior in multiagent systems informed by human behaviors.

2020

Artificial intelligence is one of the fundamental pillars on which the video game development is settled. For this reason, there are tools used in the production of a video game specifically designed for the simulation of intelligence, in order to improve the behavior of nonplayer characters. However, only few companies have enough resources for dealing with innovation in the field of artificial intelligence. This causes that small companies or independent developers often have to rely on well-known techniques that are available by default in game engines or asset stores. Unfortunately, there is a lack of quality resources related to classic techniques of artificial intelligence. To solve this problem, we have develop a tool for Unreal Engine that allows automated planning for non-player characters in a simple way, using a Goal-Oriented Action Planning architecture. This tool has been developed as a code plugin, allowing it to be easily included in any project, and it has been publi...

In the last decades, cognitive and neuroscience findings about emotion have motivated the design of emotional-based architectures to model individuals’ behavior. Currently, we are working with a cognitive, multi-layered architecture for Agents, which provides them with emotion-influenced behavior and has been extended to model social interactions. This paper shows this architecture, focusing on its social features and how it could be used to model emotion-based agents’ social behavior. A model of a prey-predator simulation is presented as a test-bed of the architecture social layer.

L'utilisation des agents virtuel pour le coaching social a connu une forte croissance ces dernires annes. Dans ce domaine, l'agent virtuel doit tre capable d'exprimer diffrentes attitudes sociales pour permettre l'utilisateur de s'entraner surmonter des situations de la vie relle. Dans cet article, nous proposons un modle d'attitudes sociales qui permet un agent virtuel de raisonner sur l'attitude sociale la plus approprie exprimer au cours d'une interaction avec l'utilisateur, en s'appuyant sur un modle d'agent affectif. L'expression de cette attitude se fait travers le comportement nonverbal.

Modeling Simulation and Optimization - Focus on Applications, 2010

Proceedings of Artificial Intelligence and Interactive …, 2009

Learning Character Behaviors using Agent Modeling in Games Richard Zhao, Duane Szafron Department of Computing Science, University of Alberta Edmonton, Alberta, Canada T6G 2E8 {rxzhao, duane} @cs.ualberta.ca ... Smith, M., Lee-Urban, S., Muñoz-Avila, H. 2007. ...

Procedia Computer Science, 2017

The paper describes and discusses processes needed for human emotional behaviour simulation, in particular, emotion incorporation into rational thinking, as well as presents corresponding agent architecture. Such system would enable various application fields, perhaps one of the most important being enhancing smart devices with emotions. Decreasing frequency of social contact has become an urgent issue, particularly among young people. Emotional and social intelligence are however highly desired set of skills which is impossible to develop without interacting with others. Although this problem has been acknowledged, and there are some efforts to facilitate social contact, e.g., by augmented virtual reality games, that is still not enough. There is a need to develop environment that would allow learning exactly social and emotional skills. This ongoing research aims at developing intelligent agents that are able to express and incorporate affects into rational processes.

2003

ABSTRACT A number of recent, highly successful games have shown that there is a demand for the personalities, moods, and relationships of Non Player Characters'(NPCs) to be made the focus of game-play. In order for this shift of focus to take place, agent architectures used to create NPCs must be augmented with models of these aspects of characters' personae. These models must then be used to drive characters' behaviour.

Psychology, Pedagogy, and Assessment in Serious Games

Serious Games rely on interactive systems to provide an efficient communication medium between the tutor and the user. Designing and implementing such medium is a multi-disciplinary task that aims at an environment that engages the user in a learning activity. User engagement is significantly related to the users’ sense of immersion or his willingness to accept the reality proposed by a game environment. This is a very relevant research topic for Artificial Intelligence (AI), since it requires computational systems to generate believable behaviors that can promote the users’ willingness to enter and engage in the game environment. In order to do this, AI research has been relying on social sciences, in particular psychology and sociology models, to ground the creation of computational models for non-player characters that behave according to the users’ expectations. In this chapter, the authors present some of the most relevant NPC research contributions following this approach.

Current computer-generated actors (CGAs) demonstrate several shortfalls that may enable human opponents to rapidly identify and defeat CGAs; a situation that results in an inadequate, and often negative, training experience. Our research is intended to correct some of these deficiencies by inserting into CGAs reasoning qualities that allow the portrayal of more human-like behaviors. The work we report was conducted in the context of developing a prototype Distributed Mission Training Integrated Threat Environment (DMTITE) system. To allow the portrayal of more human-like behaviors, we incorporated a combat psychology model into our CGA framework. The DMTITE combat psychology model is a mathematical, scalable, and computable approach to describing psychological functions affecting performance in combat. The ultimate goal for implementing this model within the DMTITE architecture is to provide a training arena that forces human participants to engage DMTITE CGAs using realistic tactic...