In this paper, we present an adaptive and scalable Web search system, based on a multi-agent reactive architecture, which drew inspiration from biological researches on the ant foraging behavior. Its target is to search autonomously information on particular topics, in huge hypertextual collections, such as the Web, exploiting the outstanding properties of the agent architectures. The algorithm has proven to be robust against environmental alterations and adaptive to user's information need changes, discovering valuable evaluation results from standard Web collections
A new ranking algorithm is here proposed, besed on Swarm Intelligence, more specifically on ACO-ANT ...
We propose an approach based on Swarm Intelligence - more specifically on Ant Colony Optimization (A...
With the rapid growth of the Web, users are often faced with the problem of information overload and...
In this paper, we present an adaptive and scalable Web search system, based on a multi-agent reactiv...
This work introduces an adaptive Web search system, based on a reactive agent architecture, which dr...
Abstract:- With the increasing amount of information available over Internet, there is a need for a ...
In this paper we propose a new ranking algorithm based on Swarm Intelligence, more specifically on t...
Humans make lot of decisions in their day-to-day life. In order to make right decisions they need mo...
AbstractThis paper presents a multi-agent distributed framework for Swarm Intelligence (SI) based on...
Artificial Intelligence Lab, Department of MIS, University of ArizonaAs part of the ongoing Illinois...
This position paper describes ongoing work on an agent-based approach to searching for information o...
Abstract: In this paper, a web search algorithm is proposed, which aims to enhance the amount of the...
Artificial Intelligence Lab, Department of MIS, University of ArizonaAs Internet services based on t...
We propose a biological-inspired algorithmic procedure for improving the precision level in respect ...
Simple organisms that live in colonies, for example ants, bees, wasps and termites have long fascina...
A new ranking algorithm is here proposed, besed on Swarm Intelligence, more specifically on ACO-ANT ...
We propose an approach based on Swarm Intelligence - more specifically on Ant Colony Optimization (A...
With the rapid growth of the Web, users are often faced with the problem of information overload and...
In this paper, we present an adaptive and scalable Web search system, based on a multi-agent reactiv...
This work introduces an adaptive Web search system, based on a reactive agent architecture, which dr...
Abstract:- With the increasing amount of information available over Internet, there is a need for a ...
In this paper we propose a new ranking algorithm based on Swarm Intelligence, more specifically on t...
Humans make lot of decisions in their day-to-day life. In order to make right decisions they need mo...
AbstractThis paper presents a multi-agent distributed framework for Swarm Intelligence (SI) based on...
Artificial Intelligence Lab, Department of MIS, University of ArizonaAs part of the ongoing Illinois...
This position paper describes ongoing work on an agent-based approach to searching for information o...
Abstract: In this paper, a web search algorithm is proposed, which aims to enhance the amount of the...
Artificial Intelligence Lab, Department of MIS, University of ArizonaAs Internet services based on t...
We propose a biological-inspired algorithmic procedure for improving the precision level in respect ...
Simple organisms that live in colonies, for example ants, bees, wasps and termites have long fascina...
A new ranking algorithm is here proposed, besed on Swarm Intelligence, more specifically on ACO-ANT ...
We propose an approach based on Swarm Intelligence - more specifically on Ant Colony Optimization (A...
With the rapid growth of the Web, users are often faced with the problem of information overload and...