A Cognitive Architecture for Agent-Based Artificial Life Simulation

2018 ◽  
pp. 197-213
Author(s):  
Ronaldo Vieira ◽  
Bruno Dembogurski ◽  
Leandro Alvim ◽  
Filipe Braida
Keyword(s):  
Artificial Life ◽  
Cognitive Architecture ◽  
Agent Based

scholarly journals A Cognitive Robotic System for a Human-Following Robot

2020 ◽  
Author(s):  
Chien Van Dang ◽  
Heungju Ahn ◽  
Hyeon C. Seo ◽  
Sang C. Lee
Keyword(s):  
Operating System ◽  
Cognitive Architecture ◽  
Current Situation ◽  
Robotic System ◽  
Target Person ◽  
Movement Direction ◽  
Agent Based ◽  
Computational Psychology ◽  
Window Approach ◽  
Cognitive Robotic

In this paper we propose a cognitive robotic system that utilizes computational psychology (the Soar cognitive architecture) and an obstacle avoidance method (modified dynamic window approach) in ROS (Robot Operating System) platform for controlling a mobile robot. This system is applied to perform a task of human-following, aiming to help the robot navigate itself to the target person avoiding collision. A cognitive agent based on Soar cognitive architecture is created to reason its current situation and make decisions on movement direction such as go-straight, turn-left or turn-right, whereas the dynamic window approach is modified to avoid collision by computing appropriate velocities for driving the robot motors. To the end, a part of implementation is presented to describes how the system works.

A Comprehensive Overview of the Applications of Artificial Life

2006 ◽  
Vol 12 (1) ◽  
pp. 153-182 ◽  
Author(s):  
Kyung-Joong Kim ◽  
Sung-Bae Cho
Keyword(s):  
Computer Graphics ◽  
Artificial Life ◽  
Simulation Software ◽  
Natural Phenomenon ◽  
Comprehensive Overview ◽  
Agent Based ◽  
Artificial Immune Network ◽  
The Status ◽  
Internet Information ◽  
Application Fields

We review the applications of artificial life (ALife), the creation of synthetic life on computers to study, simulate, and understand living systems. The definition and features of ALife are shown by application studies. ALife application fields treated include robot control, robot manufacturing, practical robots, computer graphics, natural phenomenon modeling, entertainment, games, music, economics, Internet, information processing, industrial design, simulation software, electronics, security, data mining, and telecommunications. In order to show the status of ALife application research, this review primarily features a survey of about 180 ALife application articles rather than a selected representation of a few articles. Evolutionary computation is the most popular method for designing such applications, but recently swarm intelligence, artificial immune network, and agent-based modeling have also produced results. Applications were initially restricted to the robotics and computer graphics, but presently, many different applications in engineering areas are of interest.

Norm and Social Compliance

2010 ◽  
Vol 2 (1) ◽  
pp. 50-62 ◽  
Author(s):  
Marco Campennì ◽  
Federico Cecconi ◽  
Giulia Andrighetto ◽  
Rosaria Conte
Keyword(s):  
Mental Representations ◽  
Cognitive Architecture ◽  
Agent Architecture ◽  
Agent Based ◽  
Norm Compliance ◽  
Simulation Based ◽  
The Difference ◽  
The Impact ◽  
Norm Emergence

The necessity to model the mental ingredients of norm compliance is a controversial issue within the study of norms. So far, the simulation-based study of norm emergence has shown a prevailing tendency to model norm conformity as a thoughtless behavior, emerging from social learning and imitation rather than from specific, norm-related mental representations. In this article, the opposite stance - namely, a view of norms as hybrid, two-faceted phenomena, including a behavioral/social and an internal/mental side - is taken. Such a view is aimed at accounting for the difference between norms, on one hand, and either behavioral regularities (conventions) on the other. After a brief presentation of a normative agent architecture, the preliminary results of agent-based simulations testing the impact of norm recognition and the role of normative beliefs in the emergence and stabilization of social norms are presented and discussed. We focused our attention on the effects which the use of a cognitive architecture (namely a norm recognition module) produces on the environment.

All Hazards Analysis

2006 ◽  
pp. 1-16 ◽  
Author(s):  
Daryl Essam ◽  
Hussein A. Abbass
Keyword(s):  
Problem Solving ◽  
Complex Systems ◽  
Artificial Life ◽  
Biological Warfare ◽  
Agent Based ◽  
Traditional Problem ◽  
System Components ◽  
New Perspective ◽  
Safety Applications

With the increase in the complexity of terrorism’s networks and activities, the advances in chemical and biological warfare, and the use of organized criminal activities, it is becoming apparent that dealing with this complexity is not possible with traditional problem-solving approaches. The artificial complexity area (Artificial Life, or ALife), complex systems and agent-based distillation (ABD) provide a new perspective to the problem and emphasize the importance of modeling the interaction between system components to tackle these issues. This chapter presents an introduction to Cellular Automota and ABD, and then reviews and critiques how these approaches specifically have been used to model aspects of bushfires, epidemics, biological warfare and terrorism. This chapter then extends upon previous works to present an overview of the possible use of artificial complexity models to the larger field of security and safety applications.

Sign in / Sign up

Export Citation Format

Share Document