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AGENTS
1999
Springer
14 years 1 months ago
Team-Partitioned, Opaque-Transition Reinforcement Learning
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Peter Stone, Manuela M. Veloso
DIS
1999
Springer
14 years 1 months ago
The Melting Pot of Automated Discovery: Principles for a New Science
After two decades of research on automated discovery, many principles are shaping up as a foundation of discovery science. In this paper we view discovery science as automation of ...
Jan M. Zytkow
IWANN
1999
Springer
14 years 1 months ago
Using Temporal Neighborhoods to Adapt Function Approximators in Reinforcement Learning
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
R. Matthew Kretchmar, Charles W. Anderson
AAMAS
1999
Springer
13 years 9 months ago
Fully Embodied Conversational Avatars: Making Communicative Behaviors Autonomous
: Although avatars may resemble communicative interface agents, they have for the most part not profited from recent research into autonomous embodied conversational systems. In pa...
Justine Cassell, Hannes Högni Vilhjálm...
CAI
1999
Springer
13 years 9 months ago
Context in Artificial Intelligence II. Key Elements of Contexts
: Context is the challenge for the coming years in Artificial Intelligence (AI). In the companion paper [6], we present a view of how context is considered through the literature i...
Patrick Brézillon