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» Metaphor for learning: an evolutionary algorithm
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GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
13 years 8 months ago
Evolutionary swarm design of architectural idea models
In this paper we present a swarm grammar system that makes use of bio-inspired mechanisms of reproduction, communication and construction in order to build three-dimensional struc...
Sebastian von Mammen, Christian Jacob
GECCO
2008
Springer
178views Optimization» more  GECCO 2008»
13 years 8 months ago
Agent Smith: a real-time game-playing agent for interactive dynamic games
The goal of this project is to develop an agent capable of learning and behaving autonomously and making decisions quickly in a dynamic environment. The agent’s environment is a...
Ryan K. Small
HIS
2001
13 years 9 months ago
Global Optimisation of Neural Networks Using a Deterministic Hybrid Approach
Selection of the topology of a neural network and correct parameters for the learning algorithm is a tedious task for designing an optimal artificial neural...
Gleb Beliakov, Ajith Abraham
ATAL
2009
Springer
14 years 2 months ago
State-coupled replicator dynamics
This paper introduces a new model, i.e. state-coupled replicator dynamics, expanding the link between evolutionary game theory and multiagent reinforcement learning to multistate ...
Daniel Hennes, Karl Tuyls, Matthias Rauterberg
GECCO
2010
Springer
244views Optimization» more  GECCO 2010»
13 years 8 months ago
Implicit fitness and heterogeneous preferences in the genetic algorithm
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
Justin T. H. Smith