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...
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...
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...
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...
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 ...
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
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...
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...