Browsing by Subject "Autonomous agents"

Now showing 1 - 5 of 5

Open Access
Active particles in complex and crowded environments
(American Physical Society, 2016-11) Bechinger, C.; Di Leonardo, R.; Löwen, H.; Reichhardt, C.; Volpe, G.
Differently from passive Brownian particles, active particles, also known as self-propelled Brownian particles or microswimmers and nanoswimmers, are capable of taking up energy from their environment and converting it into directed motion. Because of this constant flow of energy, their behavior can be explained and understood only within the framework of nonequilibrium physics. In the biological realm, many cells perform directed motion, for example, as a way to browse for nutrients or to avoid toxins. Inspired by these motile microorganisms, researchers have been developing artificial particles that feature similar swimming behaviors based on different mechanisms. These man-made micromachines and nanomachines hold a great potential as autonomous agents for health care, sustainability, and security applications. With a focus on the basic physical features of the interactions of self-propelled Brownian particles with a crowded and complex environment, this comprehensive review will provide a guided tour through its basic principles, the development of artificial self-propelling microparticles and nanoparticles, and their application to the study of nonequilibrium phenomena, as well as the open challenges that the field is currently facing.
Open Access
Creating crowd variation with the OCEAN personality model
(IFAAMAS, 2008-05) Durupınar, Funda; Allbeck, J.; Pelechano, N.; Badler, N.
Most current crowd simulators animate homogeneous crowds, but include underlying parameters that can be tuned to create variations within the crowd. These parameters, however, are specific to the crowd models and may be difficult for an animator or naive user to use. We propose mapping these parameters to personality traits. In this paper, we extend the HiDAC (High-Density Autonomous Crowds) system by providing each agent with a personality model in order to examine how the emergent behavior of the crowd is affected. We use the OCEAN personality model as a basis for agent psychology. To each personality trait we associate nominal behaviors; thus, specifying personality for an agent leads to an automation of the low-level parameter tuning process. We describe a plausible mapping from personality traits to existing behavior types and analyze the overall emergent crowd behaviors. Copyright © 2008, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
Open Access
Engineering sensorial delay to control phototaxis and emergent collective behaviors
(American Physical Society, 2016-01) Mijalkov, M.; McDaniel, A.; Wehr, J.; Volpe, G.
Collective motions emerging from the interaction of autonomous mobile individuals play a key role in many phenomena, from the growth of bacterial colonies to the coordination of robotic swarms. For these collective behaviors to take hold, the individuals must be able to emit, sense, and react to signals. When dealing with simple organisms and robots, these signals are necessarily very elementary; e.g., a cell might signal its presence by releasing chemicals and a robot by shining light. An additional challenge arises because the motion of the individuals is often noisy; e.g., the orientation of cells can be altered by Brownian motion and that of robots by an uneven terrain. Therefore, the emphasis is on achieving complex and tunable behaviors fromsimple autonomous agents communicating with each other in robust ways. Here, we show that the delay between sensing and reacting to a signal can determine the individual and collective long-term behavior of autonomous agents whose motion is intrinsically noisy. We experimentally demonstrate that the collective behavior of a group of phototactic robots capable of emitting a radially decaying light field can be tuned from segregation to aggregation and clustering by controlling the delay with which they change their propulsion speed in response to the light intensity they measure. We track this transition to the underlying dynamics of this system, in particular, to the ratio between the robots' sensorial delay time and the characteristic time of the robots' random reorientation. Supported by numerics, we discuss how the same mechanism can be applied to control active agents, e.g., airborne drones, moving in a three-dimensional space. Given the simplicity of this mechanism, the engineering of sensorial delay provides a potentially powerful tool to engineer and dynamically tune the behavior of large ensembles of autonomous mobile agents; furthermore, this mechanism might already be at work within living organisms such as chemotactic cells.
Open Access
How the ocean personality model affects the perception of crowds
(Institute of Electrical and Electronics Engineers, 2011) Durupınar, F.; Pelechano, N.; Allbeck, J. M.; Güdükbay, Uğur; Badler, N. I.
A personality model named High-Density Autonomous Crowds (HiDAC) simulation system provides individual differences by assigning each person different psychological and physiological traits. Users normally set these parameters to model a crowd's nonuniformity and diversity. The approach creates plausible variations in the crowd and enables novice users to dictate these variations by combining a standard personality model with a high-density crowd simulation. HiDAC addresses the simulation of local behaviors and the global wayfinding of crowds in a dynamically changing environment. It directs autonomous agents' behavior by combining geometric and psychological rules. HiDAC handles collisions through avoidance and response forces. Over long distances, the system applies collision avoidance so that agents can steer around obstacles. HiDAC assigns people specific behaviors. The number of actions they complete depends on their curiosity.
Open Access
Psychological parameters for crowd simulation: from audiences to mobs
(Institute of Electrical and Electronics Engineers, 2016) Durupınar, F.; Güdükbay, Uğur; Aman, A.; Badler, N. I.
In the social psychology literature, crowds are classified as audiences and mobs. Audiences are passive crowds, whereas mobs are active crowds with emotional, irrational and seemingly homogeneous behavior. In this study, we aim to create a system that enables the specification of different crowd types ranging from audiences to mobs. In order to achieve this goal we parametrize the common properties of mobs to create collective misbehavior. Because mobs are characterized by emotionality, we describe a framework that associates psychological components with individual agents comprising a crowd and yields emergent behaviors in the crowd as a whole. To explore the effectiveness of our framework we demonstrate two scenarios simulating the behavior of distinct mob types.