Automata-Based Multi-agent Model as a Tool for Constructing Real-Time Intelligent Control Systems

Authors:
Mariusz Flasinski
Affiliations:
-
Venue:
CEEMAS '01 Revised Papers from the Second International Workshop of Central and Eastern Europe on Multi-Agent Systems: From Theory to Practice in Multi-Agent Systems
Year:
2001

Citing 7
Cited 6

A real-time agent model in an asynchronous-object environment

MAAMAW '96 Proceedings of the 7th European workshop on Modelling autonomous agents in a multi-agent world : agents breaking away: agents breaking away
Power properties of NLC graph grammars with a polynomial membership problem

Theoretical Computer Science
Implementing soft real-time agent control

Proceedings of the fifth international conference on Autonomous agents
A Roadmap of Agent Research and Development

Autonomous Agents and Multi-Agent Systems
Intelligent Agents in the Nuclear Industry

Computer
An architecture for Real-Time Reasoning and System Control

IEEE Expert: Intelligent Systems and Their Applications
Using Archon, Part 2: Electricity Transportation Management

IEEE Expert: Intelligent Systems and Their Applications

Inference of Parsable Graph Grammars for Syntactic Pattern Recognition

Fundamenta Informaticae
Grammatical Inference as a Tool for Constructing Self-learning Syntactic Pattern Recognition-Based Agents

ICCS '08 Proceedings of the 8th international conference on Computational Science, Part III
Multi-agent System for Recognition of Hand Postures

ICCS 2009 Proceedings of the 9th International Conference on Computational Science
On the use of graph parsing for recognition of isolated hand postures of Polish Sign Language

Pattern Recognition
Parallel computing scheme for graph grammar-based syntactic pattern recognition

PPAM'09 Proceedings of the 8th international conference on Parallel processing and applied mathematics: Part I
Inference of Parsable Graph Grammars for Syntactic Pattern Recognition

Fundamenta Informaticae

Quantified Score

Hi-index	0.00

Visualization

Abstract

The multi-agent model for constructing process control intelligent systems is discussed in the paper. Agents of the model are based on three paradigms: pattern recognition, formal (string and graph) automata and rules. The efficient syntactic pattern recognition schemes are used for analysing string and graph structures that represent a structured knowledge. For string-like structures DPLL(k) quasi-context sensitive languages are applied. Graph structures are analysed with ETPL(k) graph parsers in a polynomial time. Grammatical inference algorithms can be used for both kinds of structures. It allows one to embed self-learning schemes in agents of the model.