Problem-Solving in Multi-Agent Systems: A Novel Generalized Particle Model

2006 ◽  
Author(s):  
Dianxun Shuai ◽  
Qing Shuai ◽  
Yuming Dong ◽  
Liangjun Huang
Keyword(s):  
Problem Solving ◽  
Particle Model ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

Society of Agents

2020 ◽  
pp. 160-183
Author(s):  
Steven Walczak
Keyword(s):  
Problem Solving ◽  
Information Sharing ◽  
Multi Agent Systems ◽  
New Classification ◽  
Conceptual Foundation ◽  
Agent Systems ◽  
Multi Agent ◽  
Coordination And Collaboration ◽  
Agent Coordination ◽  
New Framework

The development of multiple agent systems faces many challenges, including agent coordination and collaboration on tasks. Minsky's The Society of Mind provides a conceptual view for addressing these multi-agent system problems. A new classification ontology is introduced for comparing multi-agent systems. Next, a new framework called the Society of Agents is developed from Minsky's conceptual foundation. A Society of Agents framework-based problem-solving and a Game Society is developed and applied to the domain of single player logic puzzles and two player games. The Game Society solved 100% of presented Sudoku and Kakuro problems and never lost a tic-tac-toe game. The advantage of the Society of Agents approach is the efficient re-utilization of agents across multiple independent game domain problems and a centralized problem-solving architecture with efficient cross-agent information sharing.

Information Sharing via Active Sensing in a Multi-Agent System Inspired by Echolocating Bats

2014 ◽  
Author(s):  
Yuan Lin ◽  
Nicole Abaid
Keyword(s):  
Information Sharing ◽  
Sensory Information ◽  
Three Dimensions ◽  
Particle Model ◽  
Model Parameters ◽  
Active Sensing ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Sound Environment ◽  
Multi Agent

Current models for multi-agent systems almost exclusively employ sensory modalities such as vision where agents passively receive information from the environment. Active sensing, defined as acquiring environmental information using self-generated signals, allows widespread sharing of sensory information among agents and thus gives rise to more complex interactions within engineered multi-agent systems using radar or sonar, for example. In nature, bat swarms are animal groups that successfully employ active sensing with each individual broadcasting echolocation pulses in the environment and responding to echoes. Bats flying in groups may cope with the dense sound environment through their behavior; one hypothesized strategy is the cessation of echolocation pulses in the presence of peers and “eavesdropping”, which has been demonstrated in controlled laboratory settings. In this work, we build a self-propelled-particle model with each agent avoiding obstacles in three dimensions by emitting echolocation pulses of a unique frequency. We implement a bat-inspired rule of eavesdropping to take advantage of information sharing via active sensing while reducing the energy expenditure of the group. Through a simulation study, we show that agents indeed capitalize on peers’ pulses and echoes for obstacle avoidance and we find a maximum of this effect for a set of model parameters which relate to the domain size.

Society of Agents

2018 ◽  
Vol 14 (4) ◽  
pp. 1-23 ◽  
Author(s):  
Steven Walczak
Keyword(s):  
Problem Solving ◽  
Multi Agent Systems ◽  
New Classification ◽  
Conceptual Foundation ◽  
Agent Systems ◽  
Multi Agent ◽  
Coordination And Collaboration ◽  
Agent Coordination ◽  
New Framework ◽  
Society Of Mind

The development of multiple agent systems faces many challenges, including agent coordination and collaboration on tasks. Minsky's The Society of Mind provides a conceptual view for addressing these multi-agent system problems. A new classification ontology is introduced for comparing multi-agent systems. Next, a new framework called the Society of Agents is developed from Minsky's conceptual foundation. A Society of Agents framework-based problem-solving and a Game Society is developed and applied to the domain of single player logic puzzles and two player games. The Game Society solved 100% of presented Sudoku and Kakuro problems and never lost a tic-tac-toe game. The advantage of the Society of Agents approach is the efficient re-utilization of agents across multiple independent game domain problems and a centralized problem-solving architecture with efficient cross-agent information sharing.

Sign in / Sign up

Export Citation Format

Share Document