This paper uses partially observable Markov decision processes (POMDP’s) as a basic framework for MultiAgent planning. We distinguish three perspectives: first one is that of a...
Bharaneedharan Rathnasabapathy, Piotr J. Gmytrasie...
In Multi-Agent learning, agents must learn to select actions that maximize their utility given the action choices of the other agents. Cooperative Coevolution offers a way to evol...
This paper presents an application of Hierarchical Transition Network (HTN) planning to a squad-based military simulation. The hierarchical planner produces collaborative plans fo...
Logical formalisation of agent behaviour is desirable, not only in order to provide a clear semantics of agent-based systems, but also to provide the foundation for sophisticated r...
Nivea de Carvalho Ferreira, Michael Fisher, Wiebe ...
The paper presents a Java-based object-oriented system that offers a layered infrastructure to create the adequate framework for complex interactions between Grid components (e.g....