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ACL
1998
14 years 11 months ago
Learning Optimal Dialogue Strategies: A Case Study of a Spoken Dialogue Agent for Email
This paper describes a novel method by which a dialogue agent can learn to choose an optimal dialogue strategy. While it is widely agreed that dialogue strategies should be formul...
Marilyn A. Walker, Jeanne Frommer, Shrikanth Naray...
GECCO
2010
Springer
187views Optimization» more  GECCO 2010»
15 years 1 months ago
Evolving agent behavior in multiobjective domains using fitness-based shaping
Multiobjective evolutionary algorithms have long been applied to engineering problems. Lately they have also been used to evolve behaviors for intelligent agents. In such applicat...
Jacob Schrum, Risto Miikkulainen
AAMAS
2005
Springer
14 years 9 months ago
Learning and Exploiting Relative Weaknesses of Opponent Agents
Agents in a competitive interaction can greatly benefit from adapting to a particular adversary, rather than using the same general strategy against all opponents. One method of s...
Shaul Markovitch, Ronit Reger
CEC
2007
IEEE
15 years 4 months ago
Emergent specialization in the extended multi-rover problem
Abstract— This paper introduces the Collective Neuro Evolution (CONE) method, and compares its efficacy for designing specialization, with a conventional Neuro-Evolution (NE) me...
Geoff S. Nitschke, Martijn C. Schut, A. E. Eiben
KDD
2006
ACM
155views Data Mining» more  KDD 2006»
15 years 10 months ago
Single-pass online learning: performance, voting schemes and online feature selection
To learn concepts over massive data streams, it is essential to design inference and learning methods that operate in real time with limited memory. Online learning methods such a...
Vitor R. Carvalho, William W. Cohen