An empirical evaluation of a sentinel based approach to exception diagnosis in multi-agent systems

2006 ◽  
Author(s):  
N. Shah ◽  
K.-M. Chao ◽  
N. Godwin ◽  
A. James ◽  
C.-F. Tasi
Keyword(s):  
Empirical Evaluation ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Exception Diagnosis

scholarly journals Cooperative Information Sharing to Improve Distributed Learning in Multi-Agent Systems

2005 ◽  
Vol 24 ◽  
pp. 407-463 ◽  
Author(s):  
P. S. Dutta ◽  
N. R. Jennings ◽  
L. Moreau
Keyword(s):  
Information Sharing ◽  
Formal Analysis ◽  
Empirical Evaluation ◽  
Task Completion ◽  
Multi Agent Systems ◽  
Long Distance ◽  
State Information ◽  
Agent Systems ◽  
Systems Research ◽  
Multi Agent

Effective coordination of agents' actions in partially-observable domains is a major challenge of multi-agent systems research. To address this, many researchers have developed techniques that allow the agents to make decisions based on estimates of the states and actions of other agents that are typically learnt using some form of machine learning algorithm. Nevertheless, many of these approaches fail to provide an actual means by which the necessary information is made available so that the estimates can be learnt. To this end, we argue that cooperative communication of state information between agents is one such mechanism. However, in a dynamically changing environment, the accuracy and timeliness of this communicated information determine the fidelity of the learned estimates and the usefulness of the actions taken based on these. Given this, we propose a novel information-sharing protocol, post-task-completion sharing, for the distribution of state information. We then show, through a formal analysis, the improvement in the quality of estimates produced using our strategy over the widely used protocol of sharing information between nearest neighbours. Moreover, communication heuristics designed around our information-sharing principle are subjected to empirical evaluation along with other benchmark strategies (including Littman's Q-routing and Stone's TPOT-RL) in a simulated call-routing application. These studies, conducted across a range of environmental settings, show that, compared to the different benchmarks used, our strategy generates an improvement of up to 60% in the call connection rate; of more than 1000% in the ability to connect long-distance calls; and incurs as low as 0.25 of the message overhead.

EVALUATING PERFORMANCE AND ACCURACY OF A SENTINEL-BASED EXCEPTION DIAGNOSIS APPROACH FOR P2P AGENT SYSTEMS

2006 ◽  
Vol 07 (04) ◽  
pp. 493-506
Author(s):  
NAZARAF SHAH ◽  
NICK GODWIN ◽  
BABAK AKHGAR ◽  
JAWED SIDDIQI
Keyword(s):  
Distributed Artificial Intelligence ◽  
Centralized Control ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Trade Offs ◽  
Service Consumer ◽  
Multi Agent ◽  
Diagnosis Approach ◽  
Exception Diagnosis

Using open Multi-agent systems (MAS) to represent a peer-to-peer (P2P) organization is a complex application of distributed artificial intelligence. These systems are designed to create networked applications where each peer node contributes to the overall functionality of the application. Each agent in such systems acts as a peer and has no fixed role. In other words a peer may assume the role of either service provider or service consumer in a given interaction. The dynamics of these networked applications make them vulnerable to different kinds of exceptions. Also the absence of centralized control and changes in organizational structure gives rise to unpredictable exceptions. It becomes essential to have some exception diagnosis mechanisms in place to be able to diagnose the cause of such exceptions while preserving the autonomy of the peer agents. These mechanisms do come with some overheads. In this paper we present an evaluation of the application of our proposed sentinel based approach to exception diagnosis in P2P based MAS and also discuss the trade offs that arise in using a sentinel based approach to exception diagnosis in such systems.

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