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» Learning the required number of agents for complex tasks
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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
DAGSTUHL
2003
13 years 9 months ago
Maximizing Learning Progress: An Internal Reward System for Development
This chapter presents a generic internal reward system that drives an agent to increase the complexity of its behavior. This reward system does not reinforce a predefined task. It...
Frédéric Kaplan, Pierre-Yves Oudeyer
AIIDE
2008
13 years 10 months ago
Direction Maps for Cooperative Pathfinding
Cooperative behavior is a desired trait in many fields from computer games to robotics. Yet, achieving cooperative behavior is often difficult, as maintaining shared information a...
M. Renee Jansen, Nathan R. Sturtevant
ACL
1997
13 years 9 months ago
PARADISE: A Framework for Evaluating Spoken Dialogue Agents
This paper presents PARADISE (PARAdigm for DIalogue System Evaluation), a general framework for evaluating spoken dialogue agents. The framework decouples task requirements from a...
Marilyn A. Walker, Diane J. Litman, Candace A. Kam...
ATAL
2007
Springer
14 years 1 months ago
Estimating information value in collaborative multi-agent planning systems
This paper addresses the problem of identifying the value of information held by a teammate on a distributed, multi-agent team. It focuses on a distributed scheduling task in whic...
David Sarne, Barbara J. Grosz