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» Learning Models of Intelligent Agents
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CEC
2009
IEEE
16 years 1 months ago
Lamarckian neuroevolution for visual control in the Quake II environment
Abstract— A combination of backpropagation and neuroevolution is used to train a neural network visual controller for agents in the Quake II environment. The agents must learn to...
Matt Parker, Bobby D. Bryant
IAT
2008
IEEE
16 years 1 months ago
An Enhanced Similarity Measure for Utilizing Site Structure in Web Personalization Systems
The need for recommendation systems to ease user navigations has become evident by growth of information on the Web. There exist many approaches of learning for Web usage-based re...
Shaghayegh Sahebi, Farhad Oroumchian, Ramtin Khosr...
IAT
2007
IEEE
16 years 1 months ago
Investigating User Browsing Behavior
This paper describes our efforts to investigate factors in user browsing behavior to automatically evaluate Web pages that the user shows interest in. We developed a client site l...
Ganesan Velayathan, Seiji Yamada
ATAL
2006
Springer
15 years 10 months ago
Using multiagent teams to improve the training of incident commanders
The DEFACTO system is a multiagent based tool for training incident commanders for large scale disasters. In this paper, we highlight some of the lessons that we have learned from...
Nathan Schurr, Pratik Patil, Frederic H. Pighin, M...
174
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AAAI
2007
15 years 9 months ago
Enabling Domain-Awareness for a Generic Natural Language Interface
In this paper, we present a learning-based approach for enabling domain-awareness for a generic natural language interface. Our approach automatically acquires domain knowledge fr...
Yunyao Li, Ishan Chaudhuri, Huahai Yang, Satinder ...