A Biologically Inspired Memory in a Multi-agent Based Robotic Architecture

2011 ◽  
Author(s):  
Tomas Arredondo ◽  
Patricio Castillo ◽  
Pablo Benapres ◽  
Javiera Quiroz ◽  
Miguel Torres
Keyword(s):  
Biologically Inspired ◽  
Agent Based ◽  
Multi Agent ◽  
Robotic Architecture

Bats Versus Bugs: Collective Behavior of Prey Decreases Predation in a Biologically-Inspired Multi-Agent System

2013 ◽  
Author(s):  
Yuan Lin ◽  
Nicole Abaid
Keyword(s):  
Collective Behavior ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Biologically Inspired ◽  
Agent Based ◽  
Big Brown Bats ◽  
Hunting Success ◽  
Multi Agent ◽  
The Impact ◽  
Three Dimensional Space

In this paper, we establish an agent-based model to study the impact of collective behavior of a prey species on the hunting success of predators inspired by insectivorous bats and swarming insects, called “bugs”. In the model, we consider bats preying on bugs in a three-dimensional space with periodic boundaries. The bugs follow one of the two regimes: either they swarm randomly without interacting with peers, or they seek to align their velocity directions, which results in collective behavior. Simultaneously, the bats sense their environment with a sensing space inspired by big brown bats (Eptesicus fuscus) and independently prey on bugs. We define order parameters to measure the alignment and cohesion of the bugs and relate these quantities to the cohesion and the hunting success of the bats. Comparing the results when the bugs swarm randomly or collectively, we find that collectively behaving bugs tend to align, which results in relatively more cohesive groups. In addition, cohesion among bats is induced since bats may be attracted to the same localized bug group. Due to the fact that bats need to hunt more widely for groups of bugs, collectively behaving bugs suffer less predation compared to their randomly swarming counterparts. These findings are supported by the biological literature which cites protection from predation as a primary motivator for social behavior.

Learning From Insects to Increase Multi-Agent System Resilience: Functional Decomposition and Transfer to Support Biologically Inspired Design

2021 ◽  
Author(s):  
Isabella V. Hernandez ◽  
Bryan C. Watson ◽  
Marc Weissburg ◽  
Bert Bras
Keyword(s):  
Agent Based Modeling ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Biologically Inspired ◽  
Agent System ◽  
Agent Based ◽  
Agent Systems ◽  
Multi Agent ◽  
System Resilience ◽  
Biologically Inspired Design

Abstract Resilience is an emergent property of complex systems that describes the ability to detect, respond, and recover from adversity. Much of the modern world consists of multiple, interacting, and independent agents (i.e. Multi-Agent Systems). However, the process of improving Multi-Agent System resilience is not well understood. We seek to address this gap by applying Biologically Inspired Design to increase complex system resilience. Eusocial insect colonies are an ideal case study for system resilience. Although individual insects have low computing power, the colonies collectively perform complex tasks and demonstrate resilience. Therefore, analyzing key elements of eusocial insect colonies may offer insight on how to increase Multi-Agent System resilience. Before the strategies used in eusocial insects can be adapted for Multi-Agent Systems, however, the existing research must be identified and transferred from the biological sciences to the engineering field. These transfers often hinder or limit biologically inspired design. This paper translates the biological investigation of individual insects and colony network behavior into strategies that can be tested to increase Multi-Agent System resilience. These strategies are formulated to be applied to Agent-Based Modeling. Agent-Based Modeling has been applied to many Multi-Agent Systems including epidemiology, traffic management, and marketing. This provides a key step in the design-by-analogy process: Identifying and decoding analogies from their original context. The design principles proposed in this work provide a foundation for future testing and eventual implementation into Multi-Agent Systems.

A Multi-agent based Micro Grid Operation Method

2013 ◽  
Vol 133 (9) ◽  
pp. 1652-1657 ◽  
Author(s):  
Takeshi Nagata ◽  
Kosuke Kato ◽  
Masahiro Utatani ◽  
Yuji Ueda ◽  
Kazuya Okamoto ◽  
...  
Keyword(s):  
Agent Based ◽  
Operation Method ◽  
Multi Agent ◽  
Micro Grid ◽  
Grid Operation

Browser Security Attacks and Detection Techniques: A Case of Tabnabbing

2020 ◽  
Vol 8 (1) ◽  
pp. 33-41
Author(s):  
Dr. S. Sarika ◽  
Keyword(s):  
Credit Card ◽  
State Of The Art ◽  
Experimental Results ◽  
Detection Technique ◽  
Security Attacks ◽  
Agent Based ◽  
Detection Techniques ◽  
Browser Security ◽  
Cyber Threats ◽  
Multi Agent

Phishing is a malicious and deliberate act of sending counterfeit messages or mimicking a webpage. The goal is either to steal sensitive credentials like login information and credit card details or to install malware on a victim’s machine. Browser-based cyber threats have become one of the biggest concerns in networked architectures. The most prolific form of browser attack is tabnabbing which happens in inactive browser tabs. In a tabnabbing attack, a fake page disguises itself as a genuine page to steal data. This paper presents a multi agent based tabnabbing detection technique. The method detects heuristic changes in a webpage when a tabnabbing attack happens and give a warning to the user. Experimental results show that the method performs better when compared with state of the art tabnabbing detection techniques.

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