Studying artificial life using a simple, general cellular model
Artificial Life
Computational mechanics of cellular automata: an example
Proceedings of the workshop on Lattice dynamics
Engineering intelligent hybrid multi-agent systems
Engineering intelligent hybrid multi-agent systems
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
Genetic Programming III: Darwinian Invention & Problem Solving
Genetic Programming III: Darwinian Invention & Problem Solving
Cellular neural networks and visual computing: foundations and applications
Cellular neural networks and visual computing: foundations and applications
Multiagent reinforcement learning using function approximation
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Evolutionary patterns of agent organizations
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Hi-index | 0.00 |
The need for intelligent systems has grown in the past decade because of the increasing demand on humans and machines to perform better. The researchers of artificial intelligence (AI) have responded to these needs with the development of intelligent hybrid systems. This paper describes the modeling language for interacting hybrid systems in which we will build a new hybrid model of cellular automata and multiagent technology. Simulations with complex behavior will be model social dynamics where the focus is on the emergence of properties of local interactions. Therefore, in our approach, cellular automata form a useful framework for the multiagent simulation model and the model will be used for traffic system which lies in coordinating the local behavior of individual agent to provide an appropriate system-level behavior in grid of interacting organisms.