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AgentWeb: Topics: Agents and Learning
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• Machine Learning in Automated Text Categorisation 2/4/00 17 - Fabrizio Sebastiani, Machine Learning in Automated Text Categorisation, 1999, submitted for publication. *paper*

• Communicating Neural Network Knowledge between Agents in a Simulated Aerial Reconnaissance System 1/31/00 12 - Quirolgico, Canfield, Finin and Smith, "Communicating NeuralNetwork Knowledge between Agents in a Simulated Aerial Reconnaissance 1st Int Symp on Agent Systems and Applications (ASA99), 1999.

• Communicating Neural Networks in a Multi-Agent Systems 1/29/00 19 - STEPHEN QUIROLGICO, PhD Dissertation, Department of Information Systems University of Maryland, Baltimore County. In this dissertation, we present a framework for communicating neural network knowledge between agents in order tomodify an agent's learning or pattern classification behavior. This framework is comprised of a specification for modelingneural network knowledge, a protocol for communicating neural network knowledge between agents, and a specification ofa multi-agent architecture for managing and using neural network knowledge among a set of distributed agents. Thisframework is applied to a simulated aerial reconnaissance system in order to show how the communication of neuralnetwork knowledge can help maintain the performance of agents tasked with recognizing images of mobile military objects.

• The JAM Project: Fraud and Intrusion Detection Using Meta-learning Agents 12/9/99 13 - The JAM Project: Fraud and Intrusion Detection Using Meta-learning Agents

• Multiagent Systems: A Survey from a Machine Learning Perspective 12/15/99 13 - by Peter Stone and Manuela Veloso , Carnegie Mellon University

• IJCAI-99 Workshop on Agents Learning About, From and With other Agents 12/15/99 11 - IJCAI-99 Workshop onAgents Learning About, From and With other Agents2 August 1999, Stockholm, Sweden

• Weka 3 - Data Mining with Open Source Machine Learning Software in Java 12/15/99 13 - Weka is a collection of machine learning algorithms forsolving real-world data mining problems. It is written inJava and runs on almost any platform.

• ADAPTEAM Project 12/15/99 12 - A project at ISI whose aim is "Developing new technology for creating model based collaborative learning agents that can share inforamtion anddynamically form teams with highly flexible organization structure."

• Learning in Multi-Agent Systems 12/15/99 13 - A collection of potentially useful sources of information about issues related to learning in multi-agentsystems.

• Safe Learning in Multi-Agent Systems 12/15/99 13

• Learning Among Self-interested Agents 12/15/99 11

• Learning Situation-Specific Coordination 12/15/99 11

• Learning Organizational Roles in a Heterogeneous Multi-agent System 12/15/99 11

• Cooperative Learning over Composite Search Spaces 12/15/99 11

• Learning in Multi-Agent Systems (WPI) 12/15/99 12

• Refinement in Multi-Agent Systems 12/15/99 12

• Learning Agents for Information Filtering/Gathering 12/15/99 12

• Novel Learning Techniques for Agent Systems 12/15/99 11

• Multi-agent Knowledge Reuse and Collective Memories 12/15/99 13

• Cooperation Among Case-based Reasoning Agents 12/15/99 11

• Federated Learning 12/15/99 12

• Data-mining industry coming of age 3/3/00 18 - A short opinion piece by Gregory Piatetsky-Shapiro which appeared in IEEE Intelligent Sytems, v14n6, Nov/Dec 1999.

• G. Weiss, ed., 1997, Distributed artificial intelligence meets machine learning - Learning in multi-agent 12/15/99 13

• Weka -- Machine Learning Software in Java 6/22/00 16 - Weka is a collection of machine learning algorithms for solving real-world data mining problems implemented in Java at the University of Waikato (NZ) and distributed under the GNU public license. it is described in the book "Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations" by Ian H. Witten and Eibe Frank (Morgan Kaufmann, 1999).

• Evolutionary Theories in the Social Sciences 9/21/00 21 - A Web site titled Evolutionary Theories in the Social Sciences (ETSS)is maintained by Johann Peter Murmann and Joe Fleischhacker atNorthwestern University.

• Machine Learning textbook slides 6/25/01 19 - Tom Mitchell made available the slides drawn from his book on ML: Machine Learning, Tom Mitchell, McGraw-Hill, 1997.