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» A Novel Artificial Life Ecosystem Environment Model
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ECAL
2001
Springer
15 years 2 months ago
Evolution of Reinforcement Learning in Uncertain Environments: Emergence of Risk-Aversion and Matching
Reinforcement learning (RL) is a fundamental process by which organisms learn to achieve a goal from interactions with the environment. Using Artificial Life techniques we derive ...
Yael Niv, Daphna Joel, Isaac Meilijson, Eytan Rupp...
ATAL
2008
Springer
14 years 11 months ago
Simulation of sensor-based tracking in Second Life
This paper describes "Second Life" as a novel type of testbed and simulation environment for sensor-based applications. Second Life is a popular virtual online world tha...
Boris Brandherm, Sebastian Ullrich, Helmut Prendin...
WSCG
2004
148views more  WSCG 2004»
14 years 11 months ago
Visualization of Dynamic Behaviour of Multi-Agent Systems
The extension of our research on analysis of a single agent or agent communities combining advanced methods of visualization with traditional AI techniques is presented in this pa...
David Rehor, Pavel Slavík, David Kadlecek, ...
ISM
2008
IEEE
159views Multimedia» more  ISM 2008»
14 years 9 months ago
Adaptive Modeling of a User's Daily Life with a Wearable Sensor Network
In an environment where the contexts of users are complex and the degree of freedom of user activity is very high, such as in daily life, several factors need to be considered for...
Hyoungnyoun Kim, Ig-Jae Kim, Hyoung-Gon Kim, Ji-Hy...
CEC
2009
IEEE
15 years 1 months ago
A model for intrinsic artificial development featuring structural feedback and emergent growth
Abstract--A model for intrinsic artificial development is introduced in this paper. The proposed model features a novel mechanism where growth emerges, rather than being triggered ...
Martin Trefzer, Tüze Kuyucu, Julian Francis M...