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PPSN
2004
Springer
14 years 2 months ago
Evolutionary Multi-agent Systems
In Multi-Agent learning, agents must learn to select actions that maximize their utility given the action choices of the other agents. Cooperative Coevolution offers a way to evol...
Pieter Jan't Hoen, Edwin D. de Jong
AAAI
2004
13 years 10 months ago
Making Better Recommendations with Online Profiling Agents
In recent years, we have witnessed the success of autonomous agents applying machine learning techniques across a wide range of applications. However, agents applying the same mac...
Danny Oh, Chew Lim Tan
GECCO
2008
Springer
128views Optimization» more  GECCO 2008»
13 years 10 months ago
Adapted Pittsburgh classifier system: building accurate strategies in non markovian environments
This paper focuses on the study of the behavior of a genetic algorithm based classifier system, the Adapted Pittsburgh Classifier System (A.P.C.S), on maze type environments con...
Gilles Énée, Mathias Péroumal...
SIGDIAL
2010
13 years 7 months ago
Adaptive Referring Expression Generation in Spoken Dialogue Systems: Evaluation with Real Users
We present new results from a real-user evaluation of a data-driven approach to learning user-adaptive referring expression generation (REG) policies for spoken dialogue systems. ...
Srinivasan Janarthanam, Oliver Lemon
ROMAN
2007
IEEE
134views Robotics» more  ROMAN 2007»
14 years 3 months ago
Learning Reward Modalities for Human-Robot-Interaction in a Cooperative Training Task
—This paper proposes a novel method of learning a users preferred reward modalities for human-robot interaction through solving a cooperative training task. A learning algorithm ...
Anja Austermann, Seiji Yamada