Sciweavers

ATAL
2007
Springer
13 years 11 months ago
Periodic real-time resource allocation for teams of progressive processing agents
In this paper, we focus on the problem of finding a periodic allocation strategy for teams of resource-bounded agents. We propose a real-time dynamic algorithm RTDA , that exploi...
Jilles Steeve Dibangoye, Abdel-Illah Mouaddib, Bra...
ATAL
2007
Springer
13 years 11 months ago
An advanced bidding agent for advertisement selection on public displays
In this paper we present an advanced bidding agent that participates in first-price sealed bid auctions to allocate advertising space on BluScreen – an experimental public adve...
Alex Rogers, Esther David, Terry R. Payne, Nichola...
ATAL
2007
Springer
13 years 11 months ago
Auction-based multi-robot task allocation in COMSTAR
Over the past few years, swarm based systems have emerged as an attractive paradigm for building large scale distributed systems composed of numerous independent but coordinating ...
Matthew Hoeing, Prithviraj Dasgupta, Plamen V. Pet...
ATAL
2007
Springer
13 years 11 months ago
Distributed task allocation in social networks
This paper proposes a new variant of the task allocation problem, where the agents are connected in a social network and tasks arrive at the agents distributed over the network. W...
Mathijs de Weerdt, Yingqian Zhang, Tomas Klos
ATAL
2007
Springer
13 years 11 months ago
The human agent virtual environment
In this paper we describe a multi-agent simulation called the Human Agent Virtual Environment (or HAVE). HAVE is a test bed to explore agent-environment interaction in multiagent ...
Michael Papasimeon, Adrian R. Pearce, Simon Goss
ATAL
2007
Springer
13 years 11 months ago
Batch reinforcement learning in a complex domain
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
Shivaram Kalyanakrishnan, Peter Stone
ATAL
2007
Springer
13 years 11 months ago
Convergence and rate of convergence of a simple ant model
We present a simple ant model that solves a discrete foraging problem. We describe simulations and provide a complete convergence analysis: we show that the ant population compute...
Amine M. Boumaza, Bruno Scherrer
ATAL
2007
Springer
13 years 11 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone