Sciweavers

AGENTS
1999
Springer
13 years 8 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
AGENTS
1999
Springer
13 years 8 months ago
On Being a Teammate: Experiences Acquired in the design of RoboCup Teams
Increasingly, multi-agent systems are being designed for a variety of complex, dynamic domains. E ective agent interactions in such domains raise some of most fundamental research...
Stacy Marsella, Jafar Adibi, Yaser Al-Onaizan, Gal...
AGENTS
2001
Springer
13 years 9 months ago
A multi-agent system for automated genomic annotation
Massive amounts of raw data are currently being generated by biologists while sequencing organisms. Outside of the largest, high-pro le projects such as the Human Genome Project, ...
Keith Decker, Xiaojing Zheng, Carl Schmidt
ATAL
2003
Springer
13 years 9 months ago
MONAD: a flexible architecture for multi-agent control
Research in multi-agent systems has led to the development of many multi-agent control architectures. However, we believe that there is currently no known optimal structure for mu...
Thuc Vu, Jared Go, Gal A. Kaminka, Manuela M. Velo...
ISSRE
2003
IEEE
13 years 9 months ago
DARX - A Framework For The Fault-Tolerant Support Of Agent Software
This paper presents DARX, our framework for building applications that provide adaptive fault tolerance. It relies on the fact that multi-agent platforms constitute a very strong ...
Olivier Marin, Marin Bertier, Pierre Sens
MMAS
2004
Springer
13 years 10 months ago
Agent Server Technology for Managing Millions of Agents
d to submit first an abstract (to signal your interest and contribution) and then a full paper (for review) to the workshop. All accepted papers will be published as a volume from ...
Gaku Yamamoto
ATAL
2004
Springer
13 years 10 months ago
Time-Extended Policies in Multi-Agent Reinforcement Learning
Many algorithms such as Q-learning successfully address reinforcement learning in single-agent multi-time-step problems. In addition there are methods that address reinforcement l...
Kagan Tumer, Adrian K. Agogino
ATAL
2004
Springer
13 years 10 months ago
A Multi-Agent System for Automatically Resolving Network Interoperability Problems
In this paper we present the Thistle multi-agent system Help Desk application for helping an end user solve network interoperability problems on their own.1
Joseph A. Giampapa, Katia Sycara-Cyranski, Austin ...
TARK
2005
Springer
13 years 10 months ago
Semantics for multi-agent only knowing: extended abstract
s for Multi-Agent Only Knowing (extended abstract) Arild Waaler1,2 and Bjørnar Solhaug3,4 1 Finnmark College, Norway 2 Dep. of Informatics, University of Oslo, Norway 3 SINTEF ICT...
Arild Waaler, Bjørnar Solhaug
ATAL
2005
Springer
13 years 10 months ago
Towards a theory of "local to global" in distributed multi-agent systems (I)
There is a growing need for a theory of “local to global” in distributed multi-agent systems, one which is able systematically to describe and analyze a variety of problems. T...
Daniel Yamins