With the increasing use of the internet, many problemsolving tasks such as resource allocation, scheduling, planning, and configuration pose themselves in an open setting involvi...
—Ant-based algorithms or ant colony optimization (ACO) algorithms have been applied successfully to combinatorial optimization problems. More recently, Parpinelli and colleagues ...
This paper presents a multi-agent reinforcement learning bidding approach (MARLBS) for performing multi-agent reinforcement learning. MARLBS integrates reinforcement learning, bid...
In e-marketplaces, customers specify job requests in realtime and agents form coalitions to service them. This paper proposes a protocol for self-interested agents to negotiate pr...
We discuss a rigorous unifying framework for both planning and replanning, extending an existing logic-based approach to resource-based planning. The primitive concepts in this Ac...
Roman van der Krogt, Mathijs de Weerdt, Cees Witte...
A gradient-based method for both symmetric and asymmetric multiagent reinforcement learning is introduced in this paper. Symmetric multiagent reinforcement learning addresses the ...
A prerequisite of joining an enterprise system is the ability to cope with the rigorous demands experienced within such systems. One of the most fundamental of these demands is th...
The design of a an agent system for robotics is a problem that involves aspects coming from many different disciplines (robotics, artificial intelligence, computer vision, softwa...
Massimo Cossentino, Luca Sabatucci, Antonio Chella
In this paper, we describe EMMA (E-Mail Management Assistant), an e-mail system that addresses the process of e-mail management, from initially sorting messages into virtual folde...
This paper studies how software agents influence the market behavior of human traders. Programmed traders with a passive arbitrage seeking strategy are introduced in a double auct...