Sociable Behaviors in Virtual Worlds

2011 ◽  
pp. 123-139
Author(s):  
Francisco Grimaldo ◽  
Miguel Lozano ◽  
Fernando Barber ◽  
Juan M. Orduña
Keyword(s):  
Virtual Worlds ◽  
Social Impact ◽  
Social Model ◽  
Virtual Agents ◽  
Multi Agent Systems ◽  
Artificial Society ◽  
Simulated Environment ◽  
The Social ◽  
Multi Agent ◽  
Virtual Actors

When simulating three-dimensional environments populated by virtual humanoids, immersion requires the simulation of consistent social behaviors to keep the attention of the user/s while displaying realistic scenes. However, intelligent virtual actors still lack a kind of collective or social intelligence necessary to reinforce the roles they are playing in the simulated environment (e.g. a waiter, a guide, etc). Decision making for virtual agents has been traditionally modeled under self interested assumptions, which are not suitable for social multi-agent domains. Instead, artificial society models should be introduced to provide virtual actors with socially acceptable decisions, which are needed to cover the user expectations about the roles played in the simulated scenes. This chapter reviews the sociability models oriented to simulate the ability of the agents that are part of an artificial society and, thus, interact among its members. Furthemore, it also includes a full description of a social model for multi-agent systems that allows the actors to evaluate the social impact of their actions, and then to decide how to act in accordance with the simulated society. Finally, the authors show the social outcomes obtained from the simulation of a particular 3D social scenario.

MASCARET

2011 ◽  
pp. 1137-1156
Author(s):  
Cédric Buche ◽  
Ronan Querrec ◽  
Pierre De Loor ◽  
Pierre Chevaillier
Keyword(s):  
Social Environment ◽  
Intelligent Tutoring System ◽  
Pedagogical Agents ◽  
Multi Agent Systems ◽  
Training Environment ◽  
Pedagogical Strategies ◽  
Operational Conditions ◽  
The Social ◽  
Social Abilities ◽  
Multi Agent

This study concerns virtual environments for training in operational conditions. The principal developed idea is that these environments are heterogeneous and open multi-agent systems. The MASCARET model is proposed to organize the interactions between agents and to provide them reactive, cognitive and social abilities to simulate the physical and social environment. The physical environment represents, in a realistic way, the phenomena that learners and teachers have to take into account. The social environment is simulated by agents executing collaborative and adaptive tasks. These agents realize, in team, procedures that they have to adapt to the environment. The users participate to the training environment through their avatar. In this article, we explain how we integrated, in MASCARET, models necessary to the creation of Intelligent Tutoring System. We notably incorporate pedagogical strategies and pedagogical actions. We present pedagogical agents. To validate our model, the SÉCURÉVI application for fire fighters’ training is developed.

Analysis and synthesis: multi-agent systems in the social sciences

2012 ◽  
Vol 27 (2) ◽  
pp. 123-136 ◽  
Author(s):  
Robert E. Marks
Keyword(s):  
Social Sciences ◽  
Computer Science ◽  
Common Source ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Agent Systems ◽  
The Social ◽  
Analysis And Synthesis ◽  
Multi Agent ◽  
Computational Systems

AbstractAlthough they flow from a common source, the uses of multi-agent systems (or ‘agent-based computational systems’––ACE) vary between the social sciences and computer science. The distinction can be broadly summarized as analysis versus synthesis, or explanation versus design. I compare and contrast these uses, and discuss sufficiency and necessity in simulations in general and in multi-agent systems in particular, with a computer science audience in mind.

Simulating socially intelligent agents in semantic virtual environments

2008 ◽  
Vol 23 (4) ◽  
pp. 369-388 ◽  
Author(s):  
Francisco Grimaldo ◽  
Miguel Lozano ◽  
Fernando Barber ◽  
Guillermo Vigueras
Keyword(s):  
Virtual Environments ◽  
Social Relations ◽  
Behavioral Problems ◽  
Intelligent Agents ◽  
Three Dimensional ◽  
The Other ◽  
Social Model ◽  
Virtual Agents ◽  
Artificial Society ◽  
Agent Interaction

AbstractThe simulation of synthetic humans inhabiting virtual environments is a current research topic with a great number of behavioral problems to be tackled. Semantical virtual environments (SVEs) have recently been proposed not only to ease world modeling but also to enhance the agent–object and agent–agent interaction. Thus, we propose the use of ontologies to define the world’s knowledge base and to introduce semantic levels of detail that help the sensorization of complex scenes—containing lots of interactive objects. The object taxonomy also helps to create general and reusable operativity for autonomous characters—for example, liquids can be poured from containers such as bottles. On the other hand, we use the ontology to define social relations among agents within an artificial society. These relations must be taken into account in order to display socially acceptable decisions. Therefore, we have implemented a market-based social model that reaches coordination and sociability by means of task exchanges. This paper presents a multi-agent framework oriented to simulate socially intelligent characters in SVEs. The framework has been successfully tested in three-dimensional (3D) dynamic scenarios while simulating a virtual university bar, where groups of waiters and customers interact with both the objects in the scene and the other virtual agents, finally displaying complex social behaviors.

Deployment of Multi-Agent Robotic Systems in Presence of Obstacles

2010 ◽  
Author(s):  
Ali Soltani ◽  
Hassan Sayyaadi
Keyword(s):  
Distributed Algorithm ◽  
Robotic Systems ◽  
Virtual Agents ◽  
Weber Problem ◽  
Multi Agent Systems ◽  
Median Problem ◽  
Voronoi Cells ◽  
Agent Systems ◽  
Multi Agent ◽  
Simulation Results

The deployment of multi-agent systems in presence of obstacle deals with autonomous motion of agents toward a specified target by sensing each other and boundaries of obstacles. In this paper, asynchronous, scalable, distributed algorithm is used to deploy agents. Boundaries of obstacles are modeled by virtual agents. Algorithm was implemented by solving continuous n-median problem called generalized Fermat-Weber problem. It is shown that deployment is performed when position of real agents are the geometric median of their Voronoi cells. Simulation results show the validity of the proposed algorithm very well.

scholarly journals Resource-bounded Norm Monitoring In Multi-agent Systems

2018 ◽  
Vol 62 ◽  
pp. 153-192 ◽  
Author(s):  
Natalia Criado
Keyword(s):  
Incomplete Information ◽  
Multi Agent Systems ◽  
Sociotechnical System ◽  
Agent Systems ◽  
Norm Violations ◽  
Norm Compliance ◽  
The Social ◽  
The World ◽  
Multi Agent ◽  
Bounded Norm

Norms allow system designers to specify the desired behaviour of a sociotechnical system. In this way, norms regulate what the social and technical agents in a sociotechnical system should (not) do. In this context, a vitally important question is the development of mechanisms for monitoring whether these agents comply with norms. Proposals on norm monitoring often assume that monitoring has no costs and/or that monitors have unlimited resources to observe the environment and the actions performed by agents. In this paper, we challenge this assumption and propose the first practical resource-bounded norm monitor. Our monitor is capable of selecting the resources to be deployed and use them to check norm compliance with incomplete information about the actions performed and the state of the world. We formally demonstrate the correctness and soundness of our norm monitor and study its complexity. We also demonstrate in randomised simulations and benchmark experiments that our monitor can select monitored resources effectively and efficiently, detecting more norm violations and fulfilments than other tractable optimization approaches and obtaining slightly worse results than intractable optimal approaches.

Coordinating Agent Interactions Under Open Environments

2011 ◽  
pp. 1430-1443
Author(s):  
Quan Bai ◽  
Minjie Zhang
Keyword(s):  
Multi Agent Systems ◽  
Social Ability ◽  
Agent Interactions ◽  
Interaction Protocols ◽  
The Social ◽  
Open Environments ◽  
Agent Interaction ◽  
Coloured Petri Net ◽  
Multi Agent ◽  
Rich Interaction

An intelligent agent is a reactive, proactive, autonomous, and social entity. The social ability of an agent is exercised in a multi-agent system (MAS), which constitutes a collection of such agents. Current multi-agent systems mostly work in complex, open, and dynamic environments. In an open environment, many facts, such as domain constraints, agent number, and agent relationships, are not fixed. That brings a lot of difficulties to coordinate agents’ interactions and cooperation. One major problem that impedes agent interaction is that most current agent interaction protocols are not very suitable for open environments. In this chapter, we introduce an approach to ameliorate agent interactions from two perspectives. First, the approach can enable agents to form knowledge “rich” interaction protocols by using ontologies. Second, we use coloured Petri net (CPN) based methods to enable agents to form interaction protocols dynamically, which are more suitable for agent interaction under open environments.

Coordinating Agent Interactions Under Open Environments

2006 ◽  
pp. 52-67 ◽  
Author(s):  
Quan Bai ◽  
Minjie Zhang
Keyword(s):  
Multi Agent Systems ◽  
Social Ability ◽  
Agent Interactions ◽  
Interaction Protocols ◽  
The Social ◽  
Open Environments ◽  
Agent Interaction ◽  
Coloured Petri Net ◽  
Multi Agent ◽  
Rich Interaction

An intelligent agent is a reactive, proactive, autonomous, and social entity. The social ability of an agent is exercised in a multi-agent system (MAS), which constitutes a collection of such agents. Current multi-agent systems mostly work in complex, open, and dynamic environments. In an open environment, many facts, such as domain constraints, agent number, and agent relationships, are not fixed. That brings a lot of difficulties to coordinate agents’ interactions and cooperation. One major problem that impedes agent interaction is that most current agent interaction protocols are not very suitable for open environments. In this chapter, we introduce an approach to ameliorate agent interactions from two perspectives. First, the approach can enable agents to form knowledge “rich” interaction protocols by using ontologies. Second, we use coloured Petri net (CPN) based methods to enable agents to form interaction protocols dynamically, which are more suitable for agent interaction under open environments.

EVOLUTIONARY GAMES IN MULTI-AGENT SYSTEMS OF WEIGHTED SOCIAL NETWORKS

2009 ◽  
Vol 20 (05) ◽  
pp. 701-710 ◽  
Author(s):  
WEN-BO DU ◽  
XIAN-BIN CAO ◽  
HAO-RAN ZHENG ◽  
HONG ZHOU ◽  
MAO-BIN HU
Keyword(s):  
Cooperative Behavior ◽  
Social Systems ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Evolution Of Cooperation ◽  
Multi Agent Systems ◽  
Snowdrift Game ◽  
Cooperation Level ◽  
The Social ◽  
Multi Agent

Much empirical evidence has shown realistic networks are weighted. Compared with those on unweighted networks, the dynamics on weighted network often exhibit distinctly different phenomena. In this paper, we investigate the evolutionary game dynamics (prisoner's dilemma game and snowdrift game) on a weighted social network consisted of rational agents and focus on the evolution of cooperation in the system. Simulation results show that the cooperation level is strongly affected by the weighted nature of the network. Moreover, the variation of time series has also been investigated. Our work may be helpful in understanding the cooperative behavior in the social systems.

scholarly journals ARPS: A Framework for Development, Simulation, Evaluation, and Deployment of Multi-Agent Systems

2019 ◽  
Vol 9 (21) ◽  
pp. 4483 ◽  
Author(s):  
Coelho Prado ◽  
Bauer
Keyword(s):  
Open Source ◽  
Controlled Environment ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Simulation Evaluation ◽  
Simulated Environment ◽  
Open Source Framework ◽  
Actual Environment ◽  
Multi Agent

Multi-Agent Systems (MASs) are often used to optimize the use of the resources available in an environment. A flaw during the modelling phase or an unanticipated scenario during their execution, however, can make the agents behave not as planned. As a consequence, the resources can be poorly utilized and operate sub-optimized, but it can also bring the resources into an unexpected state. Such problems can be mitigated if there is a controlled environment to test the agents’ behavior before deployment. To this end, a simulated environment provides not only a way to test the agents’ behaviour under different common scenarios but test them as well in adverse and rare state conditions. With this in mind, we have developed ARPS, an open-source framework that can be used to design computational agents, evaluate them in a simulated environment modelled after a real one, and then deploy and manage them seamlessly in the actual environment when the results of their evaluation are satisfactory.

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