Modeling the behavior of a hierarchy of command agents with context-based reasoning

Context-based reasoning is a paradigm for modeling agent behavior that is based on the idea that humans only use a small portion of their knowledge at any given time. It was specially designed to represent human tactical behavior and has been successfully implemented in systems with single agents or two agents working together. In this paper, we apply this idea in a hierarchical multi-agent system of command agents, where the agents’ actions are to command and coordinate subordinates, send reports to their superiors, and communicate with other agents at the same level. We focus on how contexts and actions can be defined for these higher level command agents and how the contexts and actions for the different command agents are related. The proposed methodology is implemented and tested for a hierarchy of command agents that are interpreting and planning an operational order at a battalion level and carrying it out in a computer generated forces environment.

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A State of Art Review on Various Aspects of Multi-Agent System

Journal of Circuits System and Computers ◽

10.1142/s0218126618300064 ◽

2018 ◽

Vol 27 (11) ◽

pp. 1830006 ◽

Cited By ~ 7

Author(s):

Renuka Kamdar ◽

Priyanka Paliwal ◽

Yogendra Kumar

Keyword(s):

Single Point ◽

Optimization Technique ◽

Future Research ◽

Multi Agent System ◽

Agent System ◽

Time Simulation ◽

The World ◽

Working Together ◽

Multi Agent

The world is witnessing a sudden shift in the paradigm of technology moving from centralized to decentralized approach. Centralized approach leads to single point of failure if any fault occurs and hence a whole system comes to rest. Hence, a decentralized approach like Multi-Agent System is trending now-a-days. A MAS is a collection of a number software entities (agents) working together in pursuit of specified tasks. This paper presents a comprehensive review on various aspects of multi-agent system. The paper explains the basic concepts of MAS with various ways it has been defined in literature. A comparison has been made on the standards to be followed for applying MAS. Classification of MAS architecture has been investigated and compared. Application of MAS in various areas of optimization technique, software platform and real-time simulation are listed in the paper. The paper draws attentions toward benefits and limitations of using MAS based on the survey done. Finally, after visualizing the wide scope of research in the field of MAS, an attempt has been made to identify future research avenues.

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EFFICIENCY ANALYSIS OF THE TIME-SHUFFLING METHOD FOR THE EVOLUTION OF AGENT BEHAVIOR

International Journal of Foundations of Computer Science ◽

10.1142/s0129054112400266 ◽

2012 ◽

Vol 23 (02) ◽

pp. 523-542

Author(s):

PATRICK EDIGER ◽

ROLF HOFFMANN

Keyword(s):

Autonomous Agents ◽

State Machine ◽

State Machines ◽

Multi Agent System ◽

Agent System ◽

Agent Behavior ◽

Local View ◽

Finite State ◽

Multi Agent ◽

Algorithm Scheme

We have analyzed the effectiveness and the efficiency of a time-shuffling method applied to an evolutionary algorithm scheme in order to optimize the behavior of autonomous agents in a multi-agent system. The multi-agent system is modeled as cellular automata (CA) because of the inherent parallelism of the model, which suits well the requirements of a system of autonomous moving agents with a local view. The task of the agents is the all-to-all communication, i.e., all agents shall communicate their initially mutually exclusive information to all other agents. The agents' uniform behavior is defined by a finite-state machine, which is evolved by a genetic algorithm (GA). 20 different initial two-dimensional environments were defined as a training set, 10 of them with border, 10 with cyclic wrap-around. The state machine was evolved (1) directly by a GA for all 20 environments, and (2) indirectly by two separate GAs for the 10 environments with border and the 10 environments with wrap-around, with a subsequent time-shuffling technique in order to integrate the good abilities from both of the separately evolved state machines. The time-shuffling technique alternates two state machines periodically. The results show that time-shuffling two separately evolved state machines is effective and much more efficient than the direct application of the GA.

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Research on Method of Property Verification of Multi-Agent System CGF Architecture Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.344.294 ◽

2013 ◽

Vol 344 ◽

pp. 294-299 ◽

Cited By ~ 1

Author(s):

Jian Chen ◽

Yan Li Yang ◽

Zhi Guo Liu

Keyword(s):

System Theory ◽

Multi Agent System ◽

System Framework ◽

Agent System ◽

Architecture Model ◽

Computer Generated Forces ◽

Multi Agent ◽

Property Verification

When Multi-agent system theory is used to the research of CGF(Computer Generated Forces), making up a correct and believable model is critical. In this article, we deal with the foundation,exit and update of Agent as well as the reconfiguration of system framework of CGF aiming at the problem of model evolvement caused by many Agent in CGF system always changing and show the validity of the model using INA.

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