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» Language Evolution by Iterated Learning With Bayesian Agents
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ICML
2006
IEEE
14 years 6 months ago
An analytic solution to discrete Bayesian reinforcement learning
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevi...
ATAL
2004
Springer
13 years 10 months ago
Decentralized Language Learning through Acting
This paper presents an algorithm for learning the meaning of messages communicated between agents that interact while acting optimally towards a cooperative goal. Our reinforcemen...
Claudia V. Goldman, Martin Allen, Shlomo Zilberste...
AGENTS
2000
Springer
13 years 9 months ago
Unsupervised clustering of robot activities: a Bayesian approach
Our goal is for robots to learn conceptual systems su cient for natural language and planning. The learning should be autonomous, without supervision. The rst steps in building a ...
Marco Ramoni, Paola Sebastiani, Paul R. Cohen
AISADM
2005
Springer
13 years 10 months ago
Evolving Agents: Communication and Cognition
Computer programming of complex systems is a time consuming effort. Results are often brittle and inflexible. Evolving, self-learning flexible multi-agent systems remain a distant ...
Leonid I. Perlovsky
ALIFE
2006
13 years 5 months ago
Understanding Linguistic Evolution by Visualizing the Emergence of Topographic Mappings
We show how cultural selection for learnability during the process of linguistic evolution can be visualized using a simple iterated learning model. Computational models of linguis...
Henry Brighton, Simon Kirby