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» Evolving autonomous agent control in the Xpilot environment
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EWLR
1999
Springer
13 years 11 months ago
Toward Seamless Transfer from Simulated to Real Worlds: A Dynamically-Rearranging Neural Network Approach
In the field of evolutionary robotics artificial neural networks are often used to construct controllers for autonomous agents, because they have useful properties such as the ab...
Peter Eggenberger, Akio Ishiguro, Seiji Tokura, To...
HIS
2004
13 years 9 months ago
Reinforcement Learning Hierarchical Neuro-Fuzzy Politree Model for Control of Autonomous Agents
: This work presents a new hybrid neuro-fuzzy model for automatic learning of actions taken by agents. The main objective of this new model is to provide an agent with intelligence...
Karla Figueiredo, Marley B. R. Vellasco, Marco Aur...
IJVR
2008
140views more  IJVR 2008»
13 years 7 months ago
Modelling Autonomous Virtual Agent Behaviours in a Virtual Environment for Risk
Our research deals with the design of a training system to support decision-making in the preparation and the management of maintenance interventions in high-risk industries namely...
Lydie Edward, Domitile Lourdeaux, Jean-Paul A. Bar...
GECCO
2007
Springer
156views Optimization» more  GECCO 2007»
14 years 1 months ago
A phenotypic analysis of GP-evolved team behaviours
This paper presents an approach to analyse the behaviours of teams of autonomous agents who work together to achieve a common goal. The agents in a team are evolved together using...
Darren Doherty, Colm O'Riordan
KI
1997
Springer
13 years 11 months ago
Agents in Proactive Environments
Abstract. Agents situated in proactive environments are acting autonomously while the environment is evolving alongside, whether or not the agents carry out any particular actions....
Dov M. Gabbay, Rolf Nossum, Michael Thielscher