Authors:
B. K. Swathi Prasad
;
Aditya G. Manjunath
and
Hariharan Ramasangu
Affiliation:
M. S. Ramaiah University of Applied Sciences, India
Keyword(s):
Formation, Pattern, Q-learning, Algorithm, Episode.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bioinformatics
;
Biomedical Engineering
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Multi-Agent Systems
;
Operational Research
;
Physical Agents
;
Simulation
;
Software Engineering
;
State Space Search
;
Symbolic Systems
Abstract:
This work provides details a simulation experiment and analysis of Q-learning applied to multi-agent systems.
Six agents interact within the environment to form hexagon, square and triangle, by reaching their specific
goal states. In the proposed approach, the agents form a hexagon and the maximum dimension of this pattern
is be reduced to form patterns with smaller dimensions. A decentralised approach of controlling the agents via
Q-Learning was adopted which reduced complexity. The agents will be able to either move forward, backward
and sideways based on the decision taken. Finally, the Q-Learning action-reward system was designed such
that the agents could exploit the system which meant that they would earn high rewards for correct actions and
negative rewards so the opposite.